From c1e30ece91b76ac307b6a412cb7b30ac6028f562 Mon Sep 17 00:00:00 2001
From: stnava <stnava@gmail.com>
Date: Sat, 31 Aug 2024 15:28:40 -0400
Subject: [PATCH] DOC: update site dox

---
 docs/articles/ANTsR.html                      |   64 +-
 .../ANTsR_files/figure-html/jacobian-1.png    |  Bin 502149 -> 501321 bytes
 .../ANTsR_files/figure-html/syn-1.png         |  Bin 275415 -> 258758 bytes
 docs/articles/RestingBOLD.html                |    2 +-
 docs/articles/deformationSimulation.html      |    2 +-
 docs/articles/iMath.html                      |    6 +-
 .../articles/multivarTemplateCoordinates.html |    2 +-
 docs/articles/simlr_interpretation.html       | 2411 +++++++++++++++--
 .../figure-html/dataintegration-1.png         |  Bin 367335 -> 382876 bytes
 .../figure-html/featureselection-1.png        |  Bin 275487 -> 279630 bytes
 .../figure-html/imp-1.png                     |  Bin 43650 -> 43945 bytes
 .../figure-html/permutation-1.png             |  Bin 81624 -> 88996 bytes
 .../figure-html/permutation2-1.png            |  Bin 84404 -> 78699 bytes
 .../figure-html/stepviz-1.png                 |  Bin 26915 -> 28039 bytes
 .../figure-html/stepviz-2.png                 |  Bin 26904 -> 27722 bytes
 .../figure-html/stepviz-3.png                 |  Bin 27881 -> 27947 bytes
 docs/pkgdown.yml                              |    2 +-
 docs/reference/antsApplyTransforms.html       |   10 +-
 docs/reference/antspymm_simlr.html            |   14 +-
 docs/reference/antsrGetPointerName.html       |    4 +-
 docs/reference/as.antsMatrix.html             |    6 +-
 docs/reference/brackets.html                  |   36 +-
 docs/reference/buildTemplate.html             |    2 +-
 .../fitBsplineObjectToScatteredData.html      |    1 -
 docs/reference/imagesToMatrix.html            |    2 +-
 docs/reference/index.html                     |   10 +-
 docs/reference/kmeansSegmentation.html        |    8 +-
 docs/reference/labelStats.html                |    8 +-
 docs/reference/n3BiasFieldCorrection2.html    |   12 +-
 docs/reference/n4BiasFieldCorrection.html     |   12 +-
 docs/reference/plotPrettyGraph.html           |    2 +-
 docs/reference/read_simlr_data_frames.html    |   10 +-
 docs/reference/simlr.html                     |    2 +-
 docs/reference/sparseRegression.html          |    4 -
 docs/reference/write_simlr_data_frames.html   |    4 +-
 docs/sitemap.xml                              |    3 +
 vignettes/simlr_interpretation.Rmd            |   23 +-
 37 files changed, 2270 insertions(+), 392 deletions(-)

diff --git a/docs/articles/ANTsR.html b/docs/articles/ANTsR.html
index 770255c6..a2d8d400 100644
--- a/docs/articles/ANTsR.html
+++ b/docs/articles/ANTsR.html
@@ -88,7 +88,7 @@ <h1 data-toc-skip>Transformations and statistical representations
                         <h4 data-toc-skip class="author">Brian B.
 Avants</h4>
             
-            <h4 data-toc-skip class="date">2024-08-13</h4>
+            <h4 data-toc-skip class="date">2024-08-31</h4>
       
       
       <div class="hidden name"><code>ANTsR.Rmd</code></div>
@@ -190,8 +190,6 @@ <h3 id="data-organization-and-access-in-antsr">Data organization and access in A
 <span><span class="co">##   Direction           : 1 0 0 1 </span></span>
 <span><span class="co">##   Filename           : /Users/stnava/Library/R/arm64/4.3/library/ANTsRCore/extdata/r16slice.jpg</span></span></code></pre>
 <p>Take a quick look at the image.</p>
-<pre><code><span><span class="co">## Warning in fun(libname, pkgname): couldn't connect to display</span></span>
-<span><span class="co">## "/private/tmp/com.apple.launchd.eGFfXWyHAN/org.xquartz:0"</span></span></code></pre>
 <p><img src="ANTsR_files/figure-html/basic_plot-1.png" width="700"></p>
 </div>
 <div class="section level3">
@@ -247,7 +245,7 @@ <h3 id="basic-antsr-functionality">Basic ANTs<em>R</em> functionality<a class="a
 representation necessary for mapping. Below is an example of how we
 access this type of image and see its geometry. Check
 <code>antsImageWrite</code> for the primary supported I/O.</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">mnifilename</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/getANTsRData.html">getANTsRData</a></span><span class="op">(</span><span class="st">"r27"</span><span class="op">)</span></span>
 <span><span class="va">img</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/antsImageRead.html">antsImageRead</a></span><span class="op">(</span><span class="va">mnifilename</span>, pixeltype<span class="op">=</span><span class="st">"unsigned char"</span><span class="op">)</span></span>
 <span><span class="va">img</span></span></code></pre></div>
@@ -259,23 +257,23 @@ <h3 id="basic-antsr-functionality">Basic ANTs<em>R</em> functionality<a class="a
 <span><span class="co">##   Origin              : 0 0 </span></span>
 <span><span class="co">##   Direction           : 1 0 0 1 </span></span>
 <span><span class="co">##   Filename           : /Users/stnava/Library/R/arm64/4.3/library/ANTsRCore/extdata/r27slice.jpg</span></span></code></pre>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># retval&lt;-antsImageWrite(img,mnifilename)</span></span>
 <span><span class="fu"><a href="../reference/antsImageGetSet.html">antsGetSpacing</a></span><span class="op">(</span><span class="va">img</span><span class="op">)</span></span></code></pre></div>
 <pre><code><span><span class="co">## [1] 1 1</span></span></code></pre>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/antsImageGetSet.html">antsGetDirection</a></span><span class="op">(</span><span class="va">img</span><span class="op">)</span></span></code></pre></div>
 <pre><code><span><span class="co">##      [,1] [,2]</span></span>
 <span><span class="co">## [1,]    1    0</span></span>
 <span><span class="co">## [2,]    0    1</span></span></code></pre>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/antsImageGetSet.html">antsGetOrigin</a></span><span class="op">(</span><span class="va">img</span><span class="op">)</span></span></code></pre></div>
 <pre><code><span><span class="co">## [1] 0 0</span></span></code></pre>
-<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">img</span><span class="op">[</span><span class="fl">120</span>,<span class="fl">122</span><span class="op">]</span><span class="op">)</span> <span class="co"># same type of thing in 3 or 4D</span></span></code></pre></div>
 <pre><code><span><span class="co">##      [,1]</span></span>
 <span><span class="co">## [1,]  182</span></span></code></pre>
-<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="fu"><a href="../reference/antsImageSummary.html">max</a></span><span class="op">(</span><span class="va">img</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
 <pre><code><span><span class="co">## [1] 255</span></span></code></pre>
 <p><strong>Index an image with a label</strong></p>
@@ -283,36 +281,36 @@ <h3 id="basic-antsr-functionality">Basic ANTs<em>R</em> functionality<a class="a
 a known region of an image with arbitrary shape but within a given
 intensity “zone”. We simulate this below and show a few accessors and
 type conversions.</p>
-<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">gaussimg</span><span class="op">&lt;-</span><span class="fu"><a href="https://rdrr.io/r/base/array.html" class="external-link">array</a></span><span class="op">(</span> data<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">125</span><span class="op">)</span>, dim<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">5</span>,<span class="fl">5</span>,<span class="fl">5</span><span class="op">)</span> <span class="op">)</span></span>
 <span><span class="va">arrayimg</span><span class="op">&lt;-</span><span class="fu"><a href="https://rdrr.io/r/base/array.html" class="external-link">array</a></span><span class="op">(</span> data<span class="op">=</span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">125</span><span class="op">)</span>, dim<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">5</span>,<span class="fl">5</span>,<span class="fl">5</span><span class="op">)</span> <span class="op">)</span></span>
 <span><span class="va">img</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/as.antsImage.html">as.antsImage</a></span><span class="op">(</span> <span class="va">arrayimg</span> <span class="op">)</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span> <span class="fu"><a href="../reference/antsImageSummary.html">max</a></span><span class="op">(</span><span class="va">img</span><span class="op">)</span> <span class="op">)</span></span></code></pre></div>
 <pre><code><span><span class="co">## [1] 125</span></span></code></pre>
-<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="va">img</span><span class="op">[</span> <span class="va">img</span> <span class="op">&gt;</span> <span class="fl">50</span>  <span class="op">]</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
 <pre><code><span><span class="co">## [1] 88</span></span></code></pre>
-<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># if using SUBSET using an antsImage, you must be explicit</span></span>
 <span><span class="va">sub</span> <span class="op">=</span> <span class="fu"><a href="../reference/as.array.html">as.array</a></span><span class="op">(</span><span class="va">img</span> <span class="op">&gt;=</span> <span class="fl">50</span><span class="op">)</span> <span class="op">&gt;</span> <span class="fl">0</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span> <span class="va">gaussimg</span><span class="op">[</span> <span class="va">sub</span>  <span class="op">]</span><span class="op">)</span> <span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] -0.1059751</span></span></code></pre>
+<pre><code><span><span class="co">## [1] 0.01461143</span></span></code></pre>
 <p><strong>Convert a 4D image to a matrix</strong></p>
 <p>Four dimensional images are generated and used in the same way. One
 can easily transform from 4D image to matrix and back.</p>
-<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">gaussimg</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/makeImage.html">makeImage</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">5</span>,<span class="fl">5</span>,<span class="fl">5</span>,<span class="fl">10</span><span class="op">)</span>, voxval <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">125</span><span class="op">*</span><span class="fl">10</span><span class="op">)</span>  <span class="op">)</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/dim.html" class="external-link">dim</a></span><span class="op">(</span><span class="va">gaussimg</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
 <pre><code><span><span class="co">## [1]  5  5  5 10</span></span></code></pre>
-<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">avg3d</span><span class="op">&lt;-</span><span class="fu">ANTsR</span><span class="fu">::</span><span class="fu"><a href="../reference/getAverageOfTimeSeries.html">getAverageOfTimeSeries</a></span><span class="op">(</span> <span class="va">gaussimg</span> <span class="op">)</span></span>
 <span><span class="va">mask</span> <span class="op">&lt;-</span> <span class="va">avg3d</span> <span class="op">&lt;</span> <span class="fl">0.25</span></span>
 <span><span class="va">gmat</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/timeseries2matrix.html">timeseries2matrix</a></span><span class="op">(</span> <span class="va">gaussimg</span>, <span class="va">mask</span> <span class="op">)</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/dim.html" class="external-link">dim</a></span><span class="op">(</span><span class="va">gmat</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1]  10 107</span></span></code></pre>
+<pre><code><span><span class="co">## [1]  10 103</span></span></code></pre>
 <p>If one has a mask, then one can use <code>makeImage</code> to
 generate a new image from a scalar or vector.</p>
-<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">newimg</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/makeImage.html">makeImage</a></span><span class="op">(</span> <span class="va">mask</span>, <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="va">avg3d</span><span class="op">)</span> <span class="op">)</span>    <span class="co"># from scalar</span></span>
 <span><span class="va">newimg</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/makeImage.html">makeImage</a></span><span class="op">(</span> <span class="va">mask</span>, <span class="fu"><a href="https://rdrr.io/r/base/colSums.html" class="external-link">colMeans</a></span><span class="op">(</span><span class="va">gmat</span><span class="op">)</span> <span class="op">)</span> <span class="co"># from vector</span></span></code></pre></div>
 <p><strong>Convert a list of images to a matrix</strong></p>
@@ -321,7 +319,7 @@ <h3 id="basic-antsr-functionality">Basic ANTs<em>R</em> functionality<a class="a
 images and then proceed to smooth them, store them in a list and convert
 them to a matrix after extracting the information of each image within a
 data-driven mask.</p>
-<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">nimages</span><span class="op">&lt;-</span><span class="fl">100</span></span>
 <span><span class="va">ilist</span><span class="op">&lt;-</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="op">)</span></span>
 <span><span class="kw">for</span> <span class="op">(</span> <span class="va">i</span> <span class="kw">in</span> <span class="fl">1</span><span class="op">:</span><span class="va">nimages</span> <span class="op">)</span></span>
@@ -335,11 +333,11 @@ <h3 id="basic-antsr-functionality">Basic ANTs<em>R</em> functionality<a class="a
 <span>  lowThresh<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="va">ilist</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span><span class="op">)</span>, cleanup<span class="op">=</span><span class="cn">TRUE</span> <span class="op">)</span></span>
 <span><span class="va">mat</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/imageListToMatrix.html">imageListToMatrix</a></span><span class="op">(</span> <span class="va">ilist</span>, <span class="va">mask</span> <span class="op">)</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/dim.html" class="external-link">dim</a></span><span class="op">(</span><span class="va">mat</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 100 350</span></span></code></pre>
+<pre><code><span><span class="co">## [1] 100 151</span></span></code></pre>
 <p>Once we have a matrix representation of our population, we might run
 a quick voxel-wise regression within the mask. Then we look at some
 summary statistics.</p>
-<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">mat</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/imageListToMatrix.html">imageListToMatrix</a></span><span class="op">(</span> <span class="va">ilist</span>, <span class="va">mask</span> <span class="op">)</span></span>
 <span><span class="va">age</span><span class="op">&lt;-</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/base/nrow.html" class="external-link">nrow</a></span><span class="op">(</span><span class="va">mat</span><span class="op">)</span> <span class="op">)</span> <span class="co"># simulated age</span></span>
 <span><span class="va">gender</span><span class="op">&lt;-</span><span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"F"</span>,<span class="st">"M"</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/nrow.html" class="external-link">nrow</a></span><span class="op">(</span><span class="va">mat</span><span class="op">)</span><span class="op">/</span><span class="fl">2</span> <span class="op">)</span> <span class="co"># simulated gender</span></span>
@@ -350,19 +348,19 @@ <h3 id="basic-antsr-functionality">Basic ANTs<em>R</em> functionality<a class="a
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">mdli</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
 <pre><code><span><span class="co">## [1] "fstat"      "pval.model" "beta"       "beta.std"   "beta.t"    </span></span>
 <span><span class="co">## [6] "beta.pval"</span></span></code></pre>
-<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">rownames</a></span><span class="op">(</span><span class="va">mdli</span><span class="op">$</span><span class="va">beta.t</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
 <pre><code><span><span class="co">## [1] "age"     "genderM"</span></span></code></pre>
-<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"age"</span>,<span class="fu"><a href="../reference/antsImageSummary.html">min</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/p.adjust.html" class="external-link">p.adjust</a></span><span class="op">(</span><span class="va">mdli</span><span class="op">$</span><span class="va">beta.pval</span><span class="op">[</span><span class="fl">1</span>,<span class="op">]</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] "age 0.0527761648158703"</span></span></code></pre>
-<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
+<pre><code><span><span class="co">## [1] "age 0.0306051971665773"</span></span></code></pre>
+<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"gen"</span>,<span class="fu"><a href="../reference/antsImageSummary.html">min</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/p.adjust.html" class="external-link">p.adjust</a></span><span class="op">(</span><span class="va">mdli</span><span class="op">$</span><span class="va">beta.pval</span><span class="op">[</span><span class="fl">2</span>,<span class="op">]</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
 <pre><code><span><span class="co">## [1] "gen 1"</span></span></code></pre>
 <p><strong>Write out a statistical map</strong></p>
 <p>We might also write out the images so that we can save them for later
 or look at them with other software.</p>
-<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">agebetas</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/makeImage.html">makeImage</a></span><span class="op">(</span> <span class="va">mask</span> , <span class="va">mdli</span><span class="op">$</span><span class="va">beta.t</span><span class="op">[</span><span class="fl">1</span>,<span class="op">]</span> <span class="op">)</span></span>
 <span><span class="va">returnval</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/antsImageWrite.html">antsImageWrite</a></span><span class="op">(</span> <span class="va">agebetas</span>, <span class="fu"><a href="https://rdrr.io/r/base/tempfile.html" class="external-link">tempfile</a></span><span class="op">(</span>fileext <span class="op">=</span><span class="st">'.nii.gz'</span><span class="op">)</span> <span class="op">)</span></span></code></pre></div>
 </div>
@@ -377,7 +375,7 @@ <h3 id="more-antsr-functionality">More ANTs<em>R</em> functionality<a class="anc
 model with MRF penalty <span class="citation">(B. B. Avants et al.
 2011)</span>. Note that we also bias correct the image to help it match
 our model <span class="citation">(Tustison et al. 2010)</span>.</p>
-<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">fi</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/antsImageRead.html">antsImageRead</a></span><span class="op">(</span> <span class="fu"><a href="../reference/getANTsRData.html">getANTsRData</a></span><span class="op">(</span><span class="st">"r16"</span><span class="op">)</span> ,<span class="fl">2</span><span class="op">)</span></span>
 <span><span class="va">fi</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/n3BiasFieldCorrection.html">n3BiasFieldCorrection</a></span><span class="op">(</span><span class="va">fi</span>,<span class="fl">2</span><span class="op">)</span></span>
 <span><span class="va">seg</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/kmeansSegmentation.html">kmeansSegmentation</a></span><span class="op">(</span> <span class="va">fi</span>, <span class="fl">3</span> <span class="op">)</span></span>
@@ -390,7 +388,7 @@ <h3 id="more-antsr-functionality">More ANTs<em>R</em> functionality<a class="anc
 shape or example, i.e. an atlas. Or to another individual.
 ANTs<em>R</em> provides a simple wrapper for SyN image registration
 <span class="citation">(Tustison and Avants 2013)</span>,</p>
-<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">mi</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/antsImageRead.html">antsImageRead</a></span><span class="op">(</span> <span class="fu"><a href="../reference/getANTsRData.html">getANTsRData</a></span><span class="op">(</span><span class="st">"r64"</span><span class="op">)</span> ,<span class="fl">2</span><span class="op">)</span></span>
 <span><span class="va">mytx</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/antsRegistration.html">antsRegistration</a></span><span class="op">(</span>fixed<span class="op">=</span><span class="va">fi</span> , moving<span class="op">=</span><span class="va">mi</span> ,</span>
 <span>    typeofTransform <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">'SyN'</span><span class="op">)</span><span class="op">)</span></span>
@@ -404,7 +402,7 @@ <h3 id="more-antsr-functionality">More ANTs<em>R</em> functionality<a class="anc
 contraction and expansion of the moving image (after affine
 transformation) that is needed to map to the fixed image. This
 deformation gradient is colloquially known as “the jacobian”.</p>
-<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">jac</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/createJacobianDeterminantImage.html">createJacobianDeterminantImage</a></span><span class="op">(</span><span class="va">fi</span>,<span class="va">mytx</span><span class="op">$</span><span class="va">fwdtransforms</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span>,<span class="fl">1</span><span class="op">)</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/invisible.html" class="external-link">invisible</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">jac</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
 <p><img src="ANTsR_files/figure-html/jacobian-1.png" width="700"></p>
@@ -421,7 +419,7 @@ <h3 id="more-antsr-functionality">More ANTs<em>R</em> functionality<a class="anc
 neighborhoods, which capture shape and texture, as a matrix. Here,
 extract an image neighborhood matrix representation such that we may
 analyze it at a given scale.</p>
-<div class="sourceCode" id="cb41"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">mnit</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/getANTsRData.html">getANTsRData</a></span><span class="op">(</span><span class="st">"r16"</span><span class="op">)</span></span>
 <span><span class="va">mnit</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/antsImageRead.html">antsImageRead</a></span><span class="op">(</span> <span class="va">mnit</span> <span class="op">)</span></span>
 <span><span class="va">mnit</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/resampleImage.html">resampleImage</a></span><span class="op">(</span> <span class="va">mnit</span> , <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="fl">4</span>, <span class="va">mnit</span><span class="op">@</span><span class="va">dimension</span><span class="op">)</span> <span class="op">)</span> <span class="co"># downsample</span></span>
@@ -453,7 +451,7 @@ <h3 id="more-antsr-functionality">More ANTs<em>R</em> functionality<a class="anc
 <h3 id="example-label-sets-and-data">Example label sets and data<a class="anchor" aria-label="anchor" href="#example-label-sets-and-data"></a>
 </h3>
 <p>ANTs<em>R</em> also provides AAL label <span class="citation">(Tzourio-Mazoyer et al. 2002)</span> names via:</p>
-<div class="sourceCode" id="cb43"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/data.html" class="external-link">data</a></span><span class="op">(</span><span class="va">aal</span>,package<span class="op">=</span><span class="st">'ANTsR'</span><span class="op">)</span></span>
 <span><span class="va">labs</span><span class="op">&lt;-</span><span class="fl">1</span><span class="op">:</span><span class="fl">90</span></span></code></pre></div>
 <p>with cortical labs defined by <code>labs</code>. The DKT atlas labels
@@ -488,7 +486,7 @@ <h3 id="bold-data-processing-with-antsr">BOLD data processing with ANTs<em>R</em
 use.</p>
 <p><strong>Motion correction</strong></p>
 <p>To motion correct your data, one might run:</p>
-<div class="sourceCode" id="cb44"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb43"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># get an average image</span></span>
 <span><span class="va">averageImage</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/getAverageOfTimeSeries.html">getAverageOfTimeSeries</a></span><span class="op">(</span> <span class="va">boldImage</span> <span class="op">)</span></span>
 <span><span class="va">motionCorrectionResults</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/antsMotionCalculation.html">antsMotionCalculation</a></span><span class="op">(</span> <span class="va">boldImage</span>,</span>
@@ -516,7 +514,7 @@ <h3 id="dimensionality-reduction">Dimensionality reduction<a class="anchor" aria
 al. (2014)</span>. This is the point of “eigenanatomy” which is a
 variation of sparse PCA that uses (optionally) biologically-motivated
 smoothness, locality or sparsity constraints.</p>
-<div class="sourceCode" id="cb45"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb44"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># assume you ran the population example above</span></span>
 <span><span class="va">eanat</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/sparseDecom.html">sparseDecom</a></span><span class="op">(</span> <span class="va">mat</span>, <span class="va">mask</span>, <span class="fl">0.2</span>, <span class="fl">5</span>, cthresh<span class="op">=</span><span class="fl">2</span>, its<span class="op">=</span><span class="fl">2</span> <span class="op">)</span></span>
 <span><span class="va">eanatimages</span> <span class="op">=</span> <span class="fu"><a href="../reference/matrixToImages.html">matrixToImages</a></span><span class="op">(</span> <span class="va">eanat</span><span class="op">$</span><span class="va">eig</span>, <span class="va">mask</span> <span class="op">)</span></span>
@@ -526,7 +524,7 @@ <h3 id="dimensionality-reduction">Dimensionality reduction<a class="anchor" aria
 <p>The parameters for the example above are set for fast processing. You
 can see our paper for some theory on these methods <span class="citation">(Kandel et al. 2014)</span>. A more realistic study
 setup would be</p>
-<div class="sourceCode" id="cb46"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb45"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">eanat</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/sparseDecom.html">sparseDecom</a></span><span class="op">(</span> inmatrix<span class="op">=</span><span class="va">mat</span>, inmask<span class="op">=</span><span class="va">famask</span>, nvecs<span class="op">=</span><span class="fl">50</span>,</span>
 <span>  sparseness<span class="op">=</span><span class="fl">0.005</span>, cthresh<span class="op">=</span><span class="fl">500</span>, its<span class="op">=</span><span class="fl">5</span>, mycoption<span class="op">=</span><span class="fl">0</span> <span class="op">)</span></span>
 <span><span class="va">jeanat</span><span class="op">&lt;-</span><span class="fu"><a href="../reference/joinEigenanatomy.html">joinEigenanatomy</a></span><span class="op">(</span> <span class="va">mat</span> , <span class="va">famask</span>, <span class="va">eanat</span><span class="op">$</span><span class="va">eig</span>,</span>
diff --git a/docs/articles/ANTsR_files/figure-html/jacobian-1.png b/docs/articles/ANTsR_files/figure-html/jacobian-1.png
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diff --git a/docs/articles/RestingBOLD.html b/docs/articles/RestingBOLD.html
index 7fe702ec..61ef8822 100644
--- a/docs/articles/RestingBOLD.html
+++ b/docs/articles/RestingBOLD.html
@@ -87,7 +87,7 @@ <h1 data-toc-skip>Resting BOLD (basic analyses using ANTsR)</h1>
                         <h4 data-toc-skip class="author">Jeffrey T.
 Duda, Brian B. Avants</h4>
             
-            <h4 data-toc-skip class="date">2024-08-13</h4>
+            <h4 data-toc-skip class="date">2024-08-31</h4>
       
       
       <div class="hidden name"><code>RestingBOLD.Rmd</code></div>
diff --git a/docs/articles/deformationSimulation.html b/docs/articles/deformationSimulation.html
index 12dcdd28..62320e2c 100644
--- a/docs/articles/deformationSimulation.html
+++ b/docs/articles/deformationSimulation.html
@@ -87,7 +87,7 @@ <h1 data-toc-skip>Simulate a deformation field with ANTsR</h1>
                         <h4 data-toc-skip class="author">Brian B.
 Avants, Jeffrey T. Duda</h4>
             
-            <h4 data-toc-skip class="date">2024-08-13</h4>
+            <h4 data-toc-skip class="date">2024-08-31</h4>
       
       
       <div class="hidden name"><code>deformationSimulation.Rmd</code></div>
diff --git a/docs/articles/iMath.html b/docs/articles/iMath.html
index 65268b6e..792586a5 100644
--- a/docs/articles/iMath.html
+++ b/docs/articles/iMath.html
@@ -88,7 +88,7 @@ <h1 data-toc-skip>iMath (mathematical operations inside
                         <h4 data-toc-skip class="author">Brian B.
 Avants, Arman Eshaghi, Jeffrey T. Duda</h4>
             
-            <h4 data-toc-skip class="date">2024-08-13</h4>
+            <h4 data-toc-skip class="date">2024-08-31</h4>
       
       
       <div class="hidden name"><code>iMath.Rmd</code></div>
@@ -124,9 +124,7 @@ <h2 id="basic-operations">Basic operations<a class="anchor" aria-label="anchor"
 <code class="sourceCode R"><span><span class="co">#dilating by a radius of 3 voxels</span></span>
 <span><span class="va">GDdilated</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/iMath.html">iMath</a></span><span class="op">(</span><span class="va">fi</span>,<span class="st">"GD"</span>, <span class="fl">3</span><span class="op">)</span></span>
 <span><span class="co">#to see what dilation has done</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/invisible.html" class="external-link">invisible</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">GDdilated</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#&gt; Warning in fun(libname, pkgname): couldn't connect to display</span></span>
-<span><span class="co">#&gt; "/private/tmp/com.apple.launchd.eGFfXWyHAN/org.xquartz:0"</span></span></code></pre></div>
+<span><span class="fu"><a href="https://rdrr.io/r/base/invisible.html" class="external-link">invisible</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">GDdilated</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
 <p><img src="iMath_files/figure-html/greydilate-1.png" width="700"></p>
 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co">#to see the difference a dilation can make</span></span>
diff --git a/docs/articles/multivarTemplateCoordinates.html b/docs/articles/multivarTemplateCoordinates.html
index afa116bd..11e339bd 100644
--- a/docs/articles/multivarTemplateCoordinates.html
+++ b/docs/articles/multivarTemplateCoordinates.html
@@ -88,7 +88,7 @@ <h1 data-toc-skip>multivariate template coordinates example for
                         <h4 data-toc-skip class="author">Brian B.
 Avants</h4>
             
-            <h4 data-toc-skip class="date">2024-08-13</h4>
+            <h4 data-toc-skip class="date">2024-08-31</h4>
       
       
       <div class="hidden name"><code>multivarTemplateCoordinates.Rmd</code></div>
diff --git a/docs/articles/simlr_interpretation.html b/docs/articles/simlr_interpretation.html
index daf669c1..de3564b8 100644
--- a/docs/articles/simlr_interpretation.html
+++ b/docs/articles/simlr_interpretation.html
@@ -185,24 +185,47 @@ <h4 id="step-2-apply-simlr">Step 2: Apply SiMLR<a class="anchor" aria-label="anc
 find a common representation across the views.</p>
 <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Applying SiMLR</span></span>
-<span><span class="va">constr</span><span class="op">=</span><span class="st">'Grassmannx1x1'</span></span>
-<span><span class="va">constr</span><span class="op">=</span><span class="st">'Stiefelx1x1'</span></span>
-<span><span class="va">constr</span><span class="op">=</span><span class="st">'orthox0.1x0.1'</span></span>
-<span><span class="va">prepro</span><span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"centerAndScale"</span>,<span class="st">"np"</span><span class="op">)</span></span>
-<span><span class="va">result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/simlr.html">simlr</a></span><span class="op">(</span><span class="va">matlist</span>,constraint<span class="op">=</span><span class="va">constr</span>,scale<span class="op">=</span><span class="va">prepro</span>, verbose<span class="op">=</span><span class="cn">TRUE</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] "ortho" "0.1"   "0.1"  </span></span>
-<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
-<span><span class="co">#&gt; [1] "initialDataTerm: -0.897019799238767  &lt;o&gt; mixer: svd  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.253280672320863 bestIt: 1 CE: -0.253280672320863"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.404583596933736 bestIt: 2 CE: -0.404583596933736"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.810491744310403 bestIt: 3 CE: -0.810491744310403"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.8193484051941 bestIt: 4 CE: -0.8193484051941"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.8193484051941 bestIt: 4 CE: -0.766879419521874"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.8193484051941 bestIt: 4 CE: -0.769814132925513"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.8193484051941 bestIt: 4 CE: -0.671251201612116"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.8193484051941 bestIt: 4 CE: -0.697501085762956"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.8193484051941 bestIt: 4 CE: -0.62642418606143"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.8193484051941 bestIt: 4 CE: -0.795599051601249"</span></span>
+<span><span class="va">prepro</span><span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span> <span class="st">"centerAndScale"</span>,<span class="st">"np"</span><span class="op">)</span></span>
+<span><span class="va">constr</span><span class="op">=</span><span class="st">'Stiefelx100x1'</span></span>
+<span><span class="va">constr</span><span class="op">=</span><span class="st">'orthox100x0.1'</span></span>
+<span><span class="va">constr</span><span class="op">=</span><span class="st">'Grassmannx100x1'</span></span>
+<span><span class="va">result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/simlr.html">simlr</a></span><span class="op">(</span><span class="va">matlist</span>,constraint<span class="op">=</span><span class="va">constr</span>,scale<span class="op">=</span><span class="va">prepro</span>, </span>
+<span><span class="co">#  mixAlg='pca', energyType='cca', # recommended</span></span>
+<span>  mixAlg<span class="op">=</span><span class="st">'ica'</span>, energyType<span class="op">=</span><span class="st">'regression'</span>, <span class="co"># recommended</span></span>
+<span>  iterations<span class="op">=</span><span class="fl">100</span>, verbose<span class="op">=</span><span class="cn">TRUE</span><span class="op">)</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "100"       "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.22587649229506  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 11.5414382771651 bestIt: 1 CE: 11.5414382771651 featOrth: 0.03353844511027"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 4.08621196186966 bestIt: 2 CE: 4.08621196186966 featOrth: 0.023082933646806"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.480130012297061 bestIt: 3 CE: 0.480130012297061 featOrth: 0.0041972214013653"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.284969369557556 bestIt: 4 CE: 0.284969369557556 featOrth: 0.00256466180362829"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.197477350741243 bestIt: 5 CE: 0.197477350741243 featOrth: 0.00172925074205155"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.152956643086643 bestIt: 6 CE: 0.152956643086643 featOrth: 0.00126817648498364"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.129276536254973 bestIt: 7 CE: 0.129276536254973 featOrth: 0.00103292443664437"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.116853471821099 bestIt: 8 CE: 0.116853471821099 featOrth: 0.000923304573690797"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.104517125505523 bestIt: 9 CE: 0.104517125505523 featOrth: 0.000773848839689275"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0926675474909758 bestIt: 10 CE: 0.0926675474909758 featOrth: 0.000701816846124169"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0814648228210452 bestIt: 11 CE: 0.0814648228210452 featOrth: 0.000611598205807818"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0756700143727747 bestIt: 12 CE: 0.0756700143727747 featOrth: 0.00055185742627314"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.072876354937637 bestIt: 13 CE: 0.072876354937637 featOrth: 0.00052267696092879"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0709727600961478 bestIt: 14 CE: 0.0709727600961478 featOrth: 0.000481417806626036"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0694565882517105 bestIt: 15 CE: 0.0694565882517105 featOrth: 0.00048091828621898"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0654571368522562 bestIt: 16 CE: 0.0654571368522562 featOrth: 0.000451553447053557"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0625885268655792 bestIt: 17 CE: 0.0625885268655792 featOrth: 0.000417105648538948"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.059929473613125 bestIt: 18 CE: 0.059929473613125 featOrth: 0.000415673380992614"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0599209470024873 bestIt: 19 CE: 0.0599209470024873 featOrth: 0.000407583959705913"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0591286626225656 bestIt: 20 CE: 0.0591286626225655 featOrth: 0.00039837572753728"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0561511702321401 bestIt: 21 CE: 0.0561511702321401 featOrth: 0.000376216839815028"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0459795129399537 bestIt: 22 CE: 0.0459795129399537 featOrth: 0.000283216047118631"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0407341568489698 bestIt: 23 CE: 0.0407341568489698 featOrth: 0.000234967953684687"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0377968155675031 bestIt: 24 CE: 0.0377968155675031 featOrth: 0.000194042046162887"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0377968155675031 bestIt: 24 CE: 0.0377968155675031 featOrth: 0.000194042046162887"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.0377968155675031 bestIt: 24 CE: 0.0377968155675031 featOrth: 0.000194042046162887"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0377968155675031 bestIt: 24 CE: 0.0377968155675031 featOrth: 0.000194042046162887"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0377968155675031 bestIt: 24 CE: 0.0377968155675031 featOrth: 0.000194042046162887"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0377968155675031 bestIt: 24 CE: 0.0377968155675031 featOrth: 0.000194042046162887"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0377968155675031 bestIt: 24 CE: 0.0377968155675031 featOrth: 0.000194042046162887"</span></span>
 <span></span>
 <span><span class="co"># Projecting data into the reduced space</span></span>
 <span><span class="va">p1</span> <span class="op">&lt;-</span> <span class="va">mat1</span> <span class="op"><a href="https://rdrr.io/r/base/matmult.html" class="external-link">%*%</a></span> <span class="op">(</span><span class="va">result</span><span class="op">$</span><span class="va">v</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span>
@@ -235,11 +258,11 @@ <h4 id="step-3-visualization-and-comparison">Step 3: Visualization and Compariso
 <span></span>
 <span><span class="co"># Print the results</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/cat.html" class="external-link">cat</a></span><span class="op">(</span><span class="st">"Correlation between p1 and p2:"</span>, <span class="va">cor_p1_p2</span>, <span class="st">"\n"</span><span class="op">)</span></span>
-<span><span class="co">#&gt; Correlation between p1 and p2: -0.9786008 0.4360317</span></span>
+<span><span class="co">#&gt; Correlation between p1 and p2: -0.6072009 0.5295442</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/cat.html" class="external-link">cat</a></span><span class="op">(</span><span class="st">"Correlation between p1 and p3:"</span>, <span class="va">cor_p1_p3</span>, <span class="st">"\n"</span><span class="op">)</span></span>
-<span><span class="co">#&gt; Correlation between p1 and p3: -0.9909754 0.5789666</span></span>
+<span><span class="co">#&gt; Correlation between p1 and p3: -0.78536 0.8769688</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/cat.html" class="external-link">cat</a></span><span class="op">(</span><span class="st">"Correlation between p2 and p3:"</span>, <span class="va">cor_p2_p3</span>, <span class="st">"\n"</span><span class="op">)</span></span>
-<span><span class="co">#&gt; Correlation between p2 and p3: -0.5314355 0.9941934</span></span>
+<span><span class="co">#&gt; Correlation between p2 and p3: -0.6106315 0.9156068</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/cat.html" class="external-link">cat</a></span><span class="op">(</span><span class="st">"Correlation between SVD1 and SVD2:"</span>, <span class="va">cor_svd1_svd2</span>, <span class="st">"\n"</span><span class="op">)</span></span>
 <span><span class="co">#&gt; Correlation between SVD1 and SVD2: -0.834545 0.5642089</span></span></code></pre></div>
 <div class="section level5">
@@ -299,11 +322,11 @@ <h4 id="step-4-permutation-test">Step 4: Permutation Test<a class="anchor" aria-
 <span></span>
 <span><span class="co"># Print permuted results</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/cat.html" class="external-link">cat</a></span><span class="op">(</span><span class="st">"Permuted Correlation between p1p and p2p:"</span>, <span class="va">cor_p1p_p2p</span>, <span class="st">"\n"</span><span class="op">)</span></span>
-<span><span class="co">#&gt; Permuted Correlation between p1p and p2p: -0.283758 0.0637503</span></span>
+<span><span class="co">#&gt; Permuted Correlation between p1p and p2p: -0.1859454 0.2437832</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/cat.html" class="external-link">cat</a></span><span class="op">(</span><span class="st">"Permuted Correlation between p1p and p3p:"</span>, <span class="va">cor_p1p_p3p</span>, <span class="st">"\n"</span><span class="op">)</span></span>
-<span><span class="co">#&gt; Permuted Correlation between p1p and p3p: -0.1339851 0.1661104</span></span>
+<span><span class="co">#&gt; Permuted Correlation between p1p and p3p: -0.2218706 0.2266735</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/cat.html" class="external-link">cat</a></span><span class="op">(</span><span class="st">"Permuted Correlation between p2p and p3p:"</span>, <span class="va">cor_p2p_p3p</span>, <span class="st">"\n"</span><span class="op">)</span></span>
-<span><span class="co">#&gt; Permuted Correlation between p2p and p3p: -0.3204276 0.335416</span></span></code></pre></div>
+<span><span class="co">#&gt; Permuted Correlation between p2p and p3p: -0.06200634 0.06821151</span></span></code></pre></div>
 <p>The permutation test will show if the observed correlations are
 stronger than those expected by chance.</p>
 <p>This introductory example demonstrates how SiMLR can uncover the
@@ -363,21 +386,21 @@ <h3 id="integration-of-multiple-data-types-via-dimensionality-reduction">Integra
 <span><span class="co">#&gt; lm(formula = age.1 ~ m1PC1 + m2PC1 + m3PC1, data = temp2[[1]])</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Residuals:</span></span>
-<span><span class="co">#&gt;      Min       1Q   Median       3Q      Max </span></span>
-<span><span class="co">#&gt; -1.87692 -0.44257  0.08478  0.46614  1.74734 </span></span>
+<span><span class="co">#&gt;     Min      1Q  Median      3Q     Max </span></span>
+<span><span class="co">#&gt; -2.3844 -0.5785 -0.1194  0.6110  2.1895 </span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Coefficients:</span></span>
-<span><span class="co">#&gt;             Estimate Std. Error t value Pr(&gt;|t|)    </span></span>
-<span><span class="co">#&gt; (Intercept)  0.06104    0.07252   0.842    0.402    </span></span>
-<span><span class="co">#&gt; m1PC1       -0.14758    0.21113  -0.699    0.486    </span></span>
-<span><span class="co">#&gt; m2PC1       -1.07477    0.13620  -7.891 4.83e-12 ***</span></span>
-<span><span class="co">#&gt; m3PC1       -1.69287    0.33952  -4.986 2.73e-06 ***</span></span>
+<span><span class="co">#&gt;               Estimate Std. Error t value Pr(&gt;|t|)    </span></span>
+<span><span class="co">#&gt; (Intercept)    0.06104    0.09057   0.674  0.50198    </span></span>
+<span><span class="co">#&gt; m1PC1         86.20382   16.50727   5.222 1.02e-06 ***</span></span>
+<span><span class="co">#&gt; m2PC1        319.34576  118.89762   2.686  0.00852 ** </span></span>
+<span><span class="co">#&gt; m3PC1       -148.60653   44.93363  -3.307  0.00133 ** </span></span>
 <span><span class="co">#&gt; ---</span></span>
 <span><span class="co">#&gt; Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</span></span>
 <span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt; Residual standard error: 0.7252 on 96 degrees of freedom</span></span>
-<span><span class="co">#&gt; Multiple R-squared:  0.5191, Adjusted R-squared:  0.5041 </span></span>
-<span><span class="co">#&gt; F-statistic: 34.54 on 3 and 96 DF,  p-value: 3.137e-15</span></span>
+<span><span class="co">#&gt; Residual standard error: 0.9057 on 96 degrees of freedom</span></span>
+<span><span class="co">#&gt; Multiple R-squared:  0.2501, Adjusted R-squared:  0.2266 </span></span>
+<span><span class="co">#&gt; F-statistic: 10.67 on 3 and 96 DF,  p-value: 4.069e-06</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span> <span class="va">age.2</span> <span class="op">~</span> <span class="va">m1PC1</span> <span class="op">+</span> <span class="va">m2PC1</span> <span class="op">+</span> <span class="va">m3PC1</span>, data<span class="op">=</span><span class="va">temp2</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span> <span class="op">)</span><span class="op">)</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Call:</span></span>
@@ -385,20 +408,20 @@ <h3 id="integration-of-multiple-data-types-via-dimensionality-reduction">Integra
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Residuals:</span></span>
 <span><span class="co">#&gt;      Min       1Q   Median       3Q      Max </span></span>
-<span><span class="co">#&gt; -1.98779 -0.46277 -0.01922  0.52706  1.76221 </span></span>
+<span><span class="co">#&gt; -1.00155 -0.26391  0.06496  0.26590  1.14346 </span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Coefficients:</span></span>
-<span><span class="co">#&gt;             Estimate Std. Error t value Pr(&gt;|t|)   </span></span>
-<span><span class="co">#&gt; (Intercept) -0.06212    0.07047  -0.881  0.38028   </span></span>
-<span><span class="co">#&gt; m1PC1        0.53952    0.20515   2.630  0.00995 **</span></span>
-<span><span class="co">#&gt; m2PC1       -0.20935    0.13235  -1.582  0.11698   </span></span>
-<span><span class="co">#&gt; m3PC1        0.04453    0.32991   0.135  0.89291   </span></span>
+<span><span class="co">#&gt;               Estimate Std. Error t value Pr(&gt;|t|)    </span></span>
+<span><span class="co">#&gt; (Intercept)   -0.06212    0.04237  -1.466 0.145891    </span></span>
+<span><span class="co">#&gt; m1PC1        125.84626    7.72234  16.296  &lt; 2e-16 ***</span></span>
+<span><span class="co">#&gt; m2PC1        197.18134   55.62207   3.545 0.000609 ***</span></span>
+<span><span class="co">#&gt; m3PC1       -252.25580   21.02062 -12.000  &lt; 2e-16 ***</span></span>
 <span><span class="co">#&gt; ---</span></span>
 <span><span class="co">#&gt; Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</span></span>
 <span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt; Residual standard error: 0.7047 on 96 degrees of freedom</span></span>
-<span><span class="co">#&gt; Multiple R-squared:  0.4669, Adjusted R-squared:  0.4502 </span></span>
-<span><span class="co">#&gt; F-statistic: 28.03 on 3 and 96 DF,  p-value: 4.2e-13</span></span>
+<span><span class="co">#&gt; Residual standard error: 0.4237 on 96 degrees of freedom</span></span>
+<span><span class="co">#&gt; Multiple R-squared:  0.8073, Adjusted R-squared:  0.8013 </span></span>
+<span><span class="co">#&gt; F-statistic: 134.1 on 3 and 96 DF,  p-value: &lt; 2.2e-16</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span> <span class="va">age.3</span> <span class="op">~</span> <span class="va">m1PC1</span> <span class="op">+</span> <span class="va">m2PC1</span> <span class="op">+</span> <span class="va">m3PC1</span>, data<span class="op">=</span><span class="va">temp2</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span> <span class="op">)</span><span class="op">)</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Call:</span></span>
@@ -406,20 +429,20 @@ <h3 id="integration-of-multiple-data-types-via-dimensionality-reduction">Integra
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Residuals:</span></span>
 <span><span class="co">#&gt;      Min       1Q   Median       3Q      Max </span></span>
-<span><span class="co">#&gt; -1.14340 -0.31062 -0.00963  0.27818  1.03336 </span></span>
+<span><span class="co">#&gt; -0.29992 -0.08532  0.00015  0.08359  0.32811 </span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Coefficients:</span></span>
-<span><span class="co">#&gt;             Estimate Std. Error t value Pr(&gt;|t|)    </span></span>
-<span><span class="co">#&gt; (Intercept)  0.03258    0.04689   0.695   0.4888    </span></span>
-<span><span class="co">#&gt; m1PC1        0.23151    0.13650   1.696   0.0931 .  </span></span>
-<span><span class="co">#&gt; m2PC1        1.06898    0.08806  12.140  &lt; 2e-16 ***</span></span>
-<span><span class="co">#&gt; m3PC1        1.33673    0.21951   6.090 2.33e-08 ***</span></span>
+<span><span class="co">#&gt;              Estimate Std. Error t value Pr(&gt;|t|)    </span></span>
+<span><span class="co">#&gt; (Intercept)   0.03258    0.01354   2.407    0.018 *  </span></span>
+<span><span class="co">#&gt; m1PC1        81.51622    2.46756  33.035   &lt;2e-16 ***</span></span>
+<span><span class="co">#&gt; m2PC1         1.48844   17.77317   0.084    0.933    </span></span>
+<span><span class="co">#&gt; m3PC1       350.62507    6.71681  52.201   &lt;2e-16 ***</span></span>
 <span><span class="co">#&gt; ---</span></span>
 <span><span class="co">#&gt; Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</span></span>
 <span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt; Residual standard error: 0.4689 on 96 degrees of freedom</span></span>
-<span><span class="co">#&gt; Multiple R-squared:  0.7866, Adjusted R-squared:   0.78 </span></span>
-<span><span class="co">#&gt; F-statistic:   118 on 3 and 96 DF,  p-value: &lt; 2.2e-16</span></span>
+<span><span class="co">#&gt; Residual standard error: 0.1354 on 96 degrees of freedom</span></span>
+<span><span class="co">#&gt; Multiple R-squared:  0.9822, Adjusted R-squared:  0.9817 </span></span>
+<span><span class="co">#&gt; F-statistic:  1767 on 3 and 96 DF,  p-value: &lt; 2.2e-16</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span> <span class="va">age.4</span> <span class="op">~</span> <span class="va">m1PC1</span> <span class="op">+</span> <span class="va">m2PC1</span> <span class="op">+</span> <span class="va">m3PC1</span>, data<span class="op">=</span><span class="va">temp2</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span> <span class="op">)</span><span class="op">)</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Call:</span></span>
@@ -427,41 +450,41 @@ <h3 id="integration-of-multiple-data-types-via-dimensionality-reduction">Integra
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Residuals:</span></span>
 <span><span class="co">#&gt;      Min       1Q   Median       3Q      Max </span></span>
-<span><span class="co">#&gt; -1.28560 -0.30096  0.06679  0.33574  0.88247 </span></span>
+<span><span class="co">#&gt; -1.42381 -0.37077  0.04138  0.42440  1.33062 </span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Coefficients:</span></span>
-<span><span class="co">#&gt;             Estimate Std. Error t value Pr(&gt;|t|)    </span></span>
-<span><span class="co">#&gt; (Intercept)  0.02380    0.04615   0.516    0.607    </span></span>
-<span><span class="co">#&gt; m1PC1        2.42044    0.13434  18.017   &lt;2e-16 ***</span></span>
-<span><span class="co">#&gt; m2PC1        1.04513    0.08667  12.059   &lt;2e-16 ***</span></span>
-<span><span class="co">#&gt; m3PC1        3.92198    0.21604  18.154   &lt;2e-16 ***</span></span>
+<span><span class="co">#&gt;              Estimate Std. Error t value Pr(&gt;|t|)    </span></span>
+<span><span class="co">#&gt; (Intercept)    0.0238     0.0594   0.401    0.690    </span></span>
+<span><span class="co">#&gt; m1PC1         14.8592    10.8272   1.372    0.173    </span></span>
+<span><span class="co">#&gt; m2PC1        991.2540    77.9858  12.711  &lt; 2e-16 ***</span></span>
+<span><span class="co">#&gt; m3PC1       -147.9854    29.4723  -5.021 2.37e-06 ***</span></span>
 <span><span class="co">#&gt; ---</span></span>
 <span><span class="co">#&gt; Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</span></span>
 <span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt; Residual standard error: 0.4615 on 96 degrees of freedom</span></span>
-<span><span class="co">#&gt; Multiple R-squared:  0.7894, Adjusted R-squared:  0.7828 </span></span>
-<span><span class="co">#&gt; F-statistic: 119.9 on 3 and 96 DF,  p-value: &lt; 2.2e-16</span></span>
+<span><span class="co">#&gt; Residual standard error: 0.594 on 96 degrees of freedom</span></span>
+<span><span class="co">#&gt; Multiple R-squared:  0.651,  Adjusted R-squared:  0.6401 </span></span>
+<span><span class="co">#&gt; F-statistic:  59.7 on 3 and 96 DF,  p-value: &lt; 2.2e-16</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span> <span class="va">age.5</span> <span class="op">~</span> <span class="va">m1PC1</span> <span class="op">+</span> <span class="va">m2PC1</span> <span class="op">+</span> <span class="va">m3PC1</span>, data<span class="op">=</span><span class="va">temp2</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span> <span class="op">)</span><span class="op">)</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Call:</span></span>
 <span><span class="co">#&gt; lm(formula = age.5 ~ m1PC1 + m2PC1 + m3PC1, data = temp2[[1]])</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Residuals:</span></span>
-<span><span class="co">#&gt;     Min      1Q  Median      3Q     Max </span></span>
-<span><span class="co">#&gt; -1.8581 -0.5587 -0.1209  0.5738  2.1824 </span></span>
+<span><span class="co">#&gt;      Min       1Q   Median       3Q      Max </span></span>
+<span><span class="co">#&gt; -1.74091 -0.42386  0.05677  0.51003  1.63835 </span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Coefficients:</span></span>
-<span><span class="co">#&gt;             Estimate Std. Error t value Pr(&gt;|t|)    </span></span>
-<span><span class="co">#&gt; (Intercept) -0.08199    0.08144  -1.007 0.316557    </span></span>
-<span><span class="co">#&gt; m1PC1        0.89302    0.23708   3.767 0.000285 ***</span></span>
-<span><span class="co">#&gt; m2PC1       -0.36262    0.15294  -2.371 0.019741 *  </span></span>
-<span><span class="co">#&gt; m3PC1        0.48221    0.38125   1.265 0.209006    </span></span>
+<span><span class="co">#&gt;               Estimate Std. Error t value Pr(&gt;|t|)    </span></span>
+<span><span class="co">#&gt; (Intercept)   -0.08199    0.07259  -1.130 0.261456    </span></span>
+<span><span class="co">#&gt; m1PC1        -28.32032   13.22977  -2.141 0.034836 *  </span></span>
+<span><span class="co">#&gt; m2PC1       -795.15011   95.29062  -8.344 5.28e-13 ***</span></span>
+<span><span class="co">#&gt; m3PC1        126.43925   36.01210   3.511 0.000682 ***</span></span>
 <span><span class="co">#&gt; ---</span></span>
 <span><span class="co">#&gt; Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</span></span>
 <span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt; Residual standard error: 0.8144 on 96 degrees of freedom</span></span>
-<span><span class="co">#&gt; Multiple R-squared:  0.2809, Adjusted R-squared:  0.2584 </span></span>
-<span><span class="co">#&gt; F-statistic:  12.5 on 3 and 96 DF,  p-value: 5.716e-07</span></span></code></pre></div>
+<span><span class="co">#&gt; Residual standard error: 0.7259 on 96 degrees of freedom</span></span>
+<span><span class="co">#&gt; Multiple R-squared:  0.4288, Adjusted R-squared:  0.4109 </span></span>
+<span><span class="co">#&gt; F-statistic: 24.02 on 3 and 96 DF,  p-value: 1.111e-11</span></span></code></pre></div>
 </div>
 <div class="section level3">
 <h3 id="sparse-feature-selection">Sparse Feature Selection<a class="anchor" aria-label="anchor" href="#sparse-feature-selection"></a>
@@ -515,7 +538,7 @@ <h3 id="cross-modal-prediction-or-imputation">Cross-Modal Prediction or Imputati
 <span><span class="op">}</span></span>
 <span><span class="va">impresult</span><span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span> og<span class="op">=</span><span class="va">popdf</span><span class="op">[</span>,<span class="va">imputedcols</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span>, imp<span class="op">=</span><span class="va">popdfi</span><span class="op">[</span>,<span class="va">imputedcols</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span>
 <span><span class="fu"><a href="https://rpkgs.datanovia.com/ggpubr/reference/ggscatter.html" class="external-link">ggscatter</a></span><span class="op">(</span> <span class="va">impresult</span>, <span class="st">'og'</span>, <span class="st">'imp'</span> <span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Imputed vs original data"</span>,<span class="va">imputedcols</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#&gt; Warning: Removed 4 rows containing missing values or values outside the scale range</span></span>
+<span><span class="co">#&gt; Warning: Removed 3 rows containing missing values or values outside the scale range</span></span>
 <span><span class="co">#&gt; (`geom_point()`).</span></span></code></pre></div>
 <p><img src="simlr_interpretation_files/figure-html/imp-1.png" width="700"></p>
 </div>
@@ -537,23 +560,22 @@ <h3 id="testing-significance-of-joint-relationships">Testing Significance of Joi
 <span>  constraint<span class="op">=</span><span class="va">constr</span>,scale<span class="op">=</span><span class="va">prepro</span>, </span>
 <span>  initialUMatrix<span class="op">=</span><span class="va">initu</span>,</span>
 <span>  nperms<span class="op">=</span><span class="va">np</span>, FUN<span class="op">=</span><span class="va">rvcoef</span>, verbose<span class="op">=</span><span class="cn">TRUE</span> <span class="op">)</span></span>
-<span><span class="co">#&gt; [1] "ortho" "0.1"   "0.1"  </span></span>
-<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
-<span><span class="co">#&gt; [1] "initialDataTerm: -0.892100113764282  &lt;o&gt; mixer: svd  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.650248428644519 bestIt: 1 CE: -0.650248428644519"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.650248428644519 bestIt: 1 CE: -0.481399800802654"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.650248428644519 bestIt: 1 CE: -0.476248138143961"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.650248428644519 bestIt: 1 CE: -0.471366874761084"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.677821086302228 bestIt: 5 CE: -0.677821086302228"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.838207156514181 bestIt: 6 CE: -0.838207156514181"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.838207156514181 bestIt: 6 CE: -0.784694758842972"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.838207156514181 bestIt: 6 CE: -0.820198645734556"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.838207156514181 bestIt: 6 CE: -0.462077600293351"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.871360670328648 bestIt: 10 CE: -0.871360670328648"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "100"       "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.0559578404981  &lt;o&gt; mixer: svd  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 3.1430611916353 bestIt: 1 CE: 3.1430611916353 featOrth: 0.0370056323113553"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 2.14327510013009 bestIt: 2 CE: 2.14327510013009 featOrth: 0.026570879147914"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.984722572028974 bestIt: 3 CE: 0.984722572028974 featOrth: 0.0155705913550374"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.984722572028974 bestIt: 3 CE: 0.984722572028974 featOrth: 0.0155705913550374"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.984722572028974 bestIt: 3 CE: 0.984722572028974 featOrth: 0.0155705913550374"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.984722572028974 bestIt: 3 CE: 0.984722572028974 featOrth: 0.0155705913550374"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.984722572028974 bestIt: 3 CE: 0.984722572028974 featOrth: 0.0155705913550374"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.984722572028974 bestIt: 3 CE: 0.984722572028974 featOrth: 0.0155705913550374"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.984722572028974 bestIt: 3 CE: 0.984722572028974 featOrth: 0.0155705913550374"</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">tail</a></span><span class="op">(</span> <span class="va">myperm</span><span class="op">$</span><span class="va">significance</span>, <span class="fl">2</span> <span class="op">)</span>  <span class="op">)</span></span>
-<span><span class="co">#&gt;    n   perm       m1_m2        m1_m3        m2_m3</span></span>
-<span><span class="co">#&gt; 42 3  ttest 3.88559e-50 4.317305e-47 1.329116e-52</span></span>
-<span><span class="co">#&gt; 43 3 pvalue 0.00000e+00 0.000000e+00 0.000000e+00</span></span>
+<span><span class="co">#&gt;    n   perm        m1_m2        m1_m3        m2_m3</span></span>
+<span><span class="co">#&gt; 42 3  ttest 1.879502e-64 2.627235e-46 3.749372e-51</span></span>
+<span><span class="co">#&gt; 43 3 pvalue 0.000000e+00 0.000000e+00 0.000000e+00</span></span>
 <span><span class="va">gglist</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="op">)</span></span>
 <span><span class="va">simlrmaps</span><span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="va">myperm</span><span class="op">$</span><span class="va">significance</span><span class="op">)</span><span class="op">[</span><span class="op">-</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">2</span><span class="op">)</span><span class="op">]</span></span>
 <span><span class="kw">for</span> <span class="op">(</span> <span class="va">xxx</span> <span class="kw">in</span> <span class="va">simlrmaps</span> <span class="op">)</span> <span class="op">{</span></span>
@@ -623,22 +645,22 @@ <h3 id="evaluating-machine-learning-objective-functions">Evaluating Machine Lear
 <span><span class="op">}</span></span>
 <span><span class="va">csearch</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">as.list</a></span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"none"</span>, </span>
 <span>  <span class="fu">paster</span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Grassmannx"</span>,<span class="st">"Stiefelx"</span>,<span class="st">"orthox"</span><span class="op">)</span>, </span>
-<span>    <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"10x10"</span>,<span class="st">"1x1"</span>,<span class="st">"0.1x0.1"</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
+<span>    <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"10x10"</span>,<span class="st">"100x1"</span>,<span class="st">"100x1"</span>,<span class="st">"1x1"</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
 <span><span class="co"># the 10x10 are weights on the optimization term of the energy</span></span>
 <span><span class="va">simparms</span> <span class="op">=</span> <span class="fu"><a href="../reference/simlr.parameters.html">simlr.parameters</a></span><span class="op">(</span> </span>
 <span>    nsimlr_options <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span> <span class="fl">2</span> <span class="op">)</span>,</span>
 <span>    prescaling_options <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span> </span>
 <span>            <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span> <span class="st">"robust"</span>, <span class="st">"centerAndScale"</span>,  <span class="st">"np"</span><span class="op">)</span> <span class="op">)</span>,</span>
-<span>    objectiver_options <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"cca"</span><span class="op">)</span>,</span>
-<span>    mixer_options<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"pca"</span><span class="op">)</span>, </span>
+<span>    objectiver_options <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"regression"</span>,<span class="st">'cca'</span><span class="op">)</span>,</span>
+<span>    mixer_options<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"ica"</span>,<span class="st">'pca'</span><span class="op">)</span>, </span>
 <span>    sparval_options<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>  <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.5</span>,<span class="fl">0.5</span>,<span class="fl">0.5</span><span class="op">)</span> <span class="op">)</span>,</span>
 <span>    expBeta_options <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.99</span><span class="op">)</span> <span class="op">)</span>,</span>
 <span>    positivities_options <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
 <span>            <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"positive"</span>,<span class="st">"positive"</span>,<span class="st">"positive"</span><span class="op">)</span><span class="op">)</span>,</span>
 <span>    optimus_options<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span> <span class="st">'lineSearch'</span><span class="op">)</span>,</span>
 <span>    constraint_options<span class="op">=</span><span class="va">csearch</span>,</span>
-<span>    search_type<span class="op">=</span><span class="st">"full"</span>,</span>
-<span>    num_samples<span class="op">=</span><span class="fl">5</span></span>
+<span>    search_type<span class="op">=</span><span class="st">"full"</span></span>
+<span><span class="co">#    num_samples=5</span></span>
 <span>    <span class="op">)</span></span></code></pre></div>
 <p>The <code>regularizeSimlr</code> function is used to apply
 regularization to the input matrices matlist. Regularization can help
@@ -666,7 +688,83 @@ <h3 id="evaluating-machine-learning-objective-functions">Evaluating Machine Lear
 <span>        nperms<span class="op">=</span><span class="fl">12</span>,</span>
 <span>        verbose<span class="op">=</span><span class="fl">4</span></span>
 <span>        <span class="op">)</span></span>
-<span><span class="co">#&gt; Will search: 10 parameter sets[1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; Will search: 52 parameter sets[1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "none"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "none" NA     NA    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 0.583398050406628  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.0102514748239556 bestIt: 1 CE: 0.0102514748239556 featOrth: 0.0667607032389575"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.00989712526672033 bestIt: 2 CE: 0.00989712526672033 featOrth: 0.0435349207277574"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.00966098455492624 bestIt: 3 CE: 0.00966098455492624 featOrth: 0.0718737062245701"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.00958824657043665 bestIt: 4 CE: 0.00958824657043665 featOrth: 0.052723050768759"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.00918575994224746 bestIt: 5 CE: 0.00918575994224746 featOrth: 0.042789323775297"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.00918575994224746 bestIt: 5 CE: 0.00923010160600085 featOrth: 0.0467986074148375"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.00918575994224746 bestIt: 5 CE: 0.00962177119058793 featOrth: 0.0654002868710363"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.00918575994224746 bestIt: 5 CE: 0.00961416484088604 featOrth: 0.0547616523050728"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.00918575994224746 bestIt: 5 CE: 0.00986903136781524 featOrth: 0.0582348145849807"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.00918575994224746 bestIt: 5 CE: 0.00977027960685396 featOrth: 0.0761300076775306"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.00918575994224746 bestIt: 5 CE: 0.00943510985352491 featOrth: 0.0371337987142039"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "none"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "none" NA     NA    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.923787715699613  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.681910847503995 bestIt: 1 CE: -0.681910847503995 featOrth: 0.0884326002748028"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.681910847503995 bestIt: 1 CE: -0.642975108671044 featOrth: 0.0849230469772611"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.681910847503995 bestIt: 1 CE: -0.641232997618985 featOrth: 0.0572436161483313"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.704804227730167 bestIt: 4 CE: -0.704804227730167 featOrth: 0.0768691691136011"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.966834973813831 bestIt: 5 CE: -0.966834973813832 featOrth: 0.0533582937508945"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.966834973813831 bestIt: 5 CE: -0.548469580266177 featOrth: 0.0363039174201783"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.966834973813831 bestIt: 5 CE: -0.548469580266177 featOrth: 0.0363039174201783"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.966834973813831 bestIt: 5 CE: -0.644043197453795 featOrth: 0.0362010872946781"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.966834973813831 bestIt: 5 CE: -0.964282775538944 featOrth: 0.0483778476700115"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.966834973813831 bestIt: 5 CE: -0.962306387785014 featOrth: 0.0478954688623747"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.966834973813831 bestIt: 5 CE: -0.960763294413568 featOrth: 0.0478480503008161"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "none"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "none" NA     NA    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 0.583398050406628  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.00845572196960357 bestIt: 1 CE: 0.00845572196960357 featOrth: 0.0667607032389575"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.00845572196960357 bestIt: 1 CE: 0.0087967121934184 featOrth: 0.0679366966164035"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.00845572196960357 bestIt: 1 CE: 0.00853746869047362 featOrth: 0.0636581549341637"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.00845572196960357 bestIt: 1 CE: 0.00852504590036578 featOrth: 0.0638233536479087"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.00845572196960357 bestIt: 1 CE: 0.00852854568370184 featOrth: 0.063178107177924"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.00845572196960357 bestIt: 1 CE: 0.00853172142561275 featOrth: 0.0625920644728356"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.00845572196960357 bestIt: 1 CE: 0.00853467380599137 featOrth: 0.0620782331198348"</span></span>
+<span><span class="co">#&gt; [1] "improvement"</span></span>
+<span><span class="co">#&gt;   nsimlr objectiver mixer ebber    optimus constraint final_energy prescaling1</span></span>
+<span><span class="co">#&gt; 1      2 regression   pca  0.99 lineSearch       none     20.13228      robust</span></span>
+<span><span class="co">#&gt;      prescaling2 prescaling3 sparval1 sparval2 sparval3 positivity1 positivity2</span></span>
+<span><span class="co">#&gt; 1 centerAndScale          np      0.5      0.5      0.5    positive    positive</span></span>
+<span><span class="co">#&gt;   positivity3 perm     m1_m2     m1_m3     m2_m3</span></span>
+<span><span class="co">#&gt; 1    positive    0 0.5044138 0.2953116 0.3052025</span></span>
+<span><span class="co">#&gt;              PC1        PC2</span></span>
+<span><span class="co">#&gt; m3.1 0.013392020 0.00000000</span></span>
+<span><span class="co">#&gt; m3.2 0.000000000 0.00000000</span></span>
+<span><span class="co">#&gt; m3.3 0.012007522 0.00000000</span></span>
+<span><span class="co">#&gt; m3.4 0.000000000 0.00000000</span></span>
+<span><span class="co">#&gt; m3.5 0.018620200 0.01795394</span></span>
+<span><span class="co">#&gt; m3.6 0.005912624 0.03007971</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
 <span><span class="co">#&gt; [1] "cca"</span></span>
 <span><span class="co">#&gt; [1] "pca"</span></span>
 <span><span class="co">#&gt; [1] "none"</span></span>
@@ -677,22 +775,163 @@ <h3 id="evaluating-machine-learning-objective-functions">Evaluating Machine Lear
 <span><span class="co">#&gt; [1] "none" NA     NA    </span></span>
 <span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
 <span><span class="co">#&gt; [1] "initialDataTerm: -0.923787715699613  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.358282079739464 bestIt: 1 CE: -0.358282079739464"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.46883381649157 bestIt: 2 CE: -0.46883381649157"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.796791010129841 bestIt: 3 CE: -0.796791010129841"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.799360419634454 bestIt: 4 CE: -0.799360419634454"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.82885037093229 bestIt: 5 CE: -0.82885037093229"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.82885037093229 bestIt: 5 CE: -0.822009500853158"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.82885037093229 bestIt: 5 CE: -0.822009500853158"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.82885037093229 bestIt: 5 CE: -0.787504380595427"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.831370815904379 bestIt: 9 CE: -0.831370815904379"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.840370229846114 bestIt: 10 CE: -0.840370229846114"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.840370229846114 bestIt: 10 CE: -0.769701075265139"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.840370229846114 bestIt: 10 CE: -0.734862687330073"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.840370229846114 bestIt: 10 CE: -0.734862687330073"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.840370229846114 bestIt: 10 CE: -0.717707788312638"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.840370229846114 bestIt: 10 CE: -0.695611170634912"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: -0.840370229846114 bestIt: 10 CE: -0.675723522545338"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.407702930999903 bestIt: 1 CE: -0.407702930999903 featOrth: 0.0884326002748028"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.407702930999903 bestIt: 1 CE: -0.252099439429198 featOrth: 0.0535853719038503"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.812885497564707 bestIt: 3 CE: -0.812885497564707 featOrth: 0.155964422723384"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.812885497564707 bestIt: 3 CE: -0.768949800017579 featOrth: 0.117130177544626"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.812885497564707 bestIt: 3 CE: -0.657833055667614 featOrth: 0.0842557212710104"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.851843622532129 bestIt: 6 CE: -0.851843622532129 featOrth: 0.0940287417440302"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.855577718449521 bestIt: 7 CE: -0.855577718449521 featOrth: 0.0814910708775088"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.880792309150649 bestIt: 8 CE: -0.880792309150649 featOrth: 0.090974338067911"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.919682600591653 bestIt: 9 CE: -0.919682600591653 featOrth: 0.10567725332165"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.920266020457128 bestIt: 10 CE: -0.920266020457128 featOrth: 0.105206668577923"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.920266020457128 bestIt: 10 CE: -0.918240798526631 featOrth: 0.102945084040736"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.920266020457128 bestIt: 10 CE: -0.918240798526631 featOrth: 0.102945084040736"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.920266020457128 bestIt: 10 CE: -0.58723881151041 featOrth: 0.0748887553867442"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.920266020457128 bestIt: 10 CE: -0.569374309636528 featOrth: 0.0736792324616851"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.920266020457128 bestIt: 10 CE: -0.569374309636528 featOrth: 0.0736792324616851"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: -0.920266020457128 bestIt: 10 CE: -0.528771649839351 featOrth: 0.072033952241728"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx10x10"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "10"        "10"       </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 1.25100508279622  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.237184452661408 bestIt: 1 CE: 0.237184452661408 featOrth: 2.30359310036867e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.177628284796421 bestIt: 2 CE: 0.177628284796421 featOrth: 0.00218175400736428"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.100439385053478 bestIt: 3 CE: 0.100439385053478 featOrth: 0.000762033747937794"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.0853108690922176 bestIt: 4 CE: 0.0853108690922176 featOrth: 0.000283194089042364"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.0709658345429911 bestIt: 5 CE: 0.0709658345429911 featOrth: 0.000404602275343169"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.0622861142266952 bestIt: 6 CE: 0.0622861142266952 featOrth: 0.000353553008594557"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0550855727200578 bestIt: 7 CE: 0.0550855727200578 featOrth: 0.000217127370110649"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0483257724033888 bestIt: 8 CE: 0.0483257724033888 featOrth: 0.000239149304386075"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0426194418951527 bestIt: 9 CE: 0.0426194418951527 featOrth: 0.000277440875568835"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0377358215286436 bestIt: 10 CE: 0.0377358215286436 featOrth: 0.000212920625383232"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.035330431626499 bestIt: 11 CE: 0.035330431626499 featOrth: 0.0002874361943797"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0336470415319477 bestIt: 12 CE: 0.0336470415319477 featOrth: 0.000191646304692365"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0327935098576746 bestIt: 13 CE: 0.0327935098576746 featOrth: 0.000200900701631965"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0321829413731842 bestIt: 14 CE: 0.0321829413731842 featOrth: 0.000212390705307405"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0292251756694916 bestIt: 15 CE: 0.0292251756694916 featOrth: 0.000222993486945821"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0285975579544225 bestIt: 16 CE: 0.0285975579544225 featOrth: 0.000203167663771171"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0281924111867021 bestIt: 17 CE: 0.0281924111867021 featOrth: 0.000194917441949429"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0267947780756691 bestIt: 18 CE: 0.0267947780756691 featOrth: 0.000240976070323354"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0266071857687879 bestIt: 19 CE: 0.0266071857687879 featOrth: 0.00024122692887667"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0247056793801687 bestIt: 20 CE: 0.0247056793801687 featOrth: 0.000322214923109493"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0247056793801687 bestIt: 20 CE: 0.0247056793801687 featOrth: 0.000322214923109493"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0247056793801687 bestIt: 20 CE: 0.0247056793801687 featOrth: 0.000322214923109493"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0247056793801687 bestIt: 20 CE: 0.0247056793801687 featOrth: 0.000322214923109493"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0247056793801687 bestIt: 20 CE: 0.0247056793801687 featOrth: 0.000322214923109493"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0247056793801687 bestIt: 20 CE: 0.0247056793801687 featOrth: 0.000322214923109493"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.0246116845318109 bestIt: 26 CE: 0.0246116845318109 featOrth: 0.000321275119595209"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0246116845318109 bestIt: 26 CE: 0.0246116845318109 featOrth: 0.000321275119595209"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0246116845318109 bestIt: 26 CE: 0.0246116845318109 featOrth: 0.000321275119595209"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0215108142925757 bestIt: 29 CE: 0.0215108142925757 featOrth: 0.000646254578460421"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0215108142925757 bestIt: 29 CE: 0.0215108142925757 featOrth: 0.000646254578460421"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0215108142925757 bestIt: 29 CE: 0.0215108142925757 featOrth: 0.000646254578460421"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0215108142925757 bestIt: 29 CE: 0.0215108142925757 featOrth: 0.000646254578460421"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.0215108142925757 bestIt: 29 CE: 0.0215108142925757 featOrth: 0.000646254578460421"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.0215108142925757 bestIt: 29 CE: 0.0215108142925757 featOrth: 0.000646254578460421"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.0215108142925757 bestIt: 29 CE: 0.0215108142925757 featOrth: 0.000646254578460421"</span></span>
+<span><span class="co">#&gt; [1] "improvement"</span></span>
+<span><span class="co">#&gt;   nsimlr objectiver mixer ebber    optimus      constraint final_energy</span></span>
+<span><span class="co">#&gt; 1      2 regression   ica  0.99 lineSearch Grassmannx10x10     21.56241</span></span>
+<span><span class="co">#&gt;   prescaling1    prescaling2 prescaling3 sparval1 sparval2 sparval3 positivity1</span></span>
+<span><span class="co">#&gt; 1      robust centerAndScale          np      0.5      0.5      0.5    positive</span></span>
+<span><span class="co">#&gt;   positivity2 positivity3 perm     m1_m2     m1_m3    m2_m3</span></span>
+<span><span class="co">#&gt; 1    positive    positive    0 0.6938846 0.3555743 0.437541</span></span>
+<span><span class="co">#&gt;               PC1          PC2</span></span>
+<span><span class="co">#&gt; m3.1 1.160190e-02 0.0000000000</span></span>
+<span><span class="co">#&gt; m3.2 6.997144e-05 0.0001090568</span></span>
+<span><span class="co">#&gt; m3.3 3.740359e-02 0.0000000000</span></span>
+<span><span class="co">#&gt; m3.4 0.000000e+00 0.0000000000</span></span>
+<span><span class="co">#&gt; m3.5 1.090682e-02 0.0116909065</span></span>
+<span><span class="co">#&gt; m3.6 0.000000e+00 0.0326001973</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx10x10"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "10"        "10"       </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.256180683310025  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.403162131399664 bestIt: 1 CE: -0.403162131399664 featOrth: 0.00336145297998003"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.604027710338999 bestIt: 2 CE: -0.604027710338999 featOrth: 0.00281525016511634"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.604027710338999 bestIt: 2 CE: -0.567336852179014 featOrth: 0.00186404525686447"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.604027710338999 bestIt: 2 CE: -0.602967479366712 featOrth: 0.0024843137684324"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.622356154298575 bestIt: 5 CE: -0.622356154298575 featOrth: 0.00283387923175915"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.626120748641519 bestIt: 6 CE: -0.626120748641519 featOrth: 0.00257608466697399"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.626120748641519 bestIt: 6 CE: -0.623603080545204 featOrth: 0.00334564824887162"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.626120748641519 bestIt: 6 CE: -0.623603080545204 featOrth: 0.00334564824887162"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.626120748641519 bestIt: 6 CE: -0.623603080545204 featOrth: 0.00334564824887162"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.626120748641519 bestIt: 6 CE: -0.623603080545204 featOrth: 0.00334564824887162"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.626120748641519 bestIt: 6 CE: -0.623603080545204 featOrth: 0.00334564824887162"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.792774150318934 bestIt: 12 CE: -0.792774150318934 featOrth: 0.00277913687830129"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.792774150318934 bestIt: 12 CE: -0.792344673849731 featOrth: 0.00217839385226207"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.798597657559087 bestIt: 14 CE: -0.798597657559087 featOrth: 0.00174830155460466"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.798597657559087 bestIt: 14 CE: -0.792277076833766 featOrth: 0.00165724840230397"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: -0.798597657559087 bestIt: 14 CE: -0.79798867961827 featOrth: 0.00129035596671857"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: -0.798597657559087 bestIt: 14 CE: -0.795193390255349 featOrth: 0.00129825533705678"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: -0.798597657559087 bestIt: 14 CE: -0.793023320926906 featOrth: 0.00130076172188352"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: -0.798597657559087 bestIt: 14 CE: -0.789443930397348 featOrth: 0.00131283753743851"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: -0.798597657559087 bestIt: 14 CE: -0.789443930397348 featOrth: 0.00131283753743851"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx10x10"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "10"        "10"       </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 1.25100508279622  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.237010555483456 bestIt: 1 CE: 0.237010555483456 featOrth: 2.30359310036867e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.166384964737938 bestIt: 2 CE: 0.166384964737938 featOrth: 0.000942970414049846"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.0926427844767851 bestIt: 3 CE: 0.0926427844767851 featOrth: 0.000311224624021638"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.0779647405896616 bestIt: 4 CE: 0.0779647405896616 featOrth: 0.000454673551623459"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.0643846458111018 bestIt: 5 CE: 0.0643846458111018 featOrth: 0.000453293811604207"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.0607853007000804 bestIt: 6 CE: 0.0607853007000804 featOrth: 0.000381275553675063"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0516136421826456 bestIt: 7 CE: 0.0516136421826456 featOrth: 0.000551672078236491"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0450218008463065 bestIt: 8 CE: 0.0450218008463065 featOrth: 0.000209747321969012"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.041810577582262 bestIt: 9 CE: 0.041810577582262 featOrth: 0.000223595127895771"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0358627946311294 bestIt: 10 CE: 0.0358627946311294 featOrth: 0.000385854864404967"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0335799438335706 bestIt: 11 CE: 0.0335799438335706 featOrth: 0.000233088538733437"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0308327090876032 bestIt: 12 CE: 0.0308327090876032 featOrth: 0.000301133687945096"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0303314889733687 bestIt: 13 CE: 0.0303314889733687 featOrth: 0.00021549812074918"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0300711512577661 bestIt: 14 CE: 0.0300711512577661 featOrth: 0.000213700161025347"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0286346305946391 bestIt: 15 CE: 0.0286346305946391 featOrth: 0.000277448333261432"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0286346305946391 bestIt: 15 CE: 0.0286346305946391 featOrth: 0.000277448333261432"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0286346305946391 bestIt: 15 CE: 0.0286346305946391 featOrth: 0.000277448333261432"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0226963844233598 bestIt: 18 CE: 0.0226963844233598 featOrth: 0.000553508042699336"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0226963844233598 bestIt: 18 CE: 0.0228530820770538 featOrth: 0.000553476530243937"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0222323140367165 bestIt: 20 CE: 0.0222323140367165 featOrth: 0.000552964437145945"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0222323140367165 bestIt: 20 CE: 0.0226088814323472 featOrth: 0.0005531185336545"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0222323140367165 bestIt: 20 CE: 0.022458496913351 featOrth: 0.000552783585994021"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0222323140367165 bestIt: 20 CE: 0.0223539378245985 featOrth: 0.000552847521311157"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0222323140367165 bestIt: 20 CE: 0.0231066998635607 featOrth: 0.000552948750220638"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0222323140367165 bestIt: 20 CE: 0.0230657473968752 featOrth: 0.000552830684429562"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.0211697784710775 bestIt: 26 CE: 0.0211697784710775 featOrth: 0.00055255268715628"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0211697784710775 bestIt: 26 CE: 0.0218630338597877 featOrth: 0.000552933564529659"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0211697784710775 bestIt: 26 CE: 0.0221711797290334 featOrth: 0.000552515416904157"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0211697784710775 bestIt: 26 CE: 0.0221342696847951 featOrth: 0.000552740605709478"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0211193477022873 bestIt: 30 CE: 0.0211193477022874 featOrth: 0.000552476595174642"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0211193477022873 bestIt: 30 CE: 0.0211193477022874 featOrth: 0.000552476595174642"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0211193477022873 bestIt: 30 CE: 0.0211193477022874 featOrth: 0.000552476595174642"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.0211058790588581 bestIt: 33 CE: 0.0211058790588581 featOrth: 0.000552584941424626"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.0211058790588581 bestIt: 33 CE: 0.0211058790588581 featOrth: 0.000552584941424626"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.0211058790588581 bestIt: 33 CE: 0.0211058790588581 featOrth: 0.000552584941424626"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.0211058790588581 bestIt: 33 CE: 0.0211226695578629 featOrth: 0.000552593599629494"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.0211058790588581 bestIt: 33 CE: 0.0211475849783709 featOrth: 0.000552665970777635"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.0211058790588581 bestIt: 33 CE: 0.0211619119775582 featOrth: 0.000552798860556121"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 39 bestEv: 0.0211058790588581 bestIt: 33 CE: 0.0211619119775582 featOrth: 0.000552798860556121"</span></span>
 <span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
 <span><span class="co">#&gt; [1] "cca"</span></span>
 <span><span class="co">#&gt; [1] "pca"</span></span>
@@ -704,17 +943,407 @@ <h3 id="evaluating-machine-learning-objective-functions">Evaluating Machine Lear
 <span><span class="co">#&gt; [1] "Grassmann" "10"        "10"       </span></span>
 <span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
 <span><span class="co">#&gt; [1] "initialDataTerm: -0.256180683310025  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.572332138279817 bestIt: 1 CE: -0.572332138279817"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.742869999695666 bestIt: 2 CE: -0.742869999695666"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.742869999695666 bestIt: 2 CE: -0.738929198216032"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.742869999695666 bestIt: 2 CE: -0.738929198216032"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.742869999695666 bestIt: 2 CE: -0.738929198216032"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.742869999695666 bestIt: 2 CE: -0.738929198216032"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.742869999695666 bestIt: 2 CE: -0.738929198216032"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.742869999695666 bestIt: 2 CE: -0.738929198216032"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.604061236845367 bestIt: 1 CE: -0.604061236845367 featOrth: 0.00336145297998003"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.748792135449735 bestIt: 2 CE: -0.748792135449735 featOrth: 0.00660958135986834"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.748792135449735 bestIt: 2 CE: -0.748792135449735 featOrth: 0.00660958135986834"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.748792135449735 bestIt: 2 CE: -0.748792135449735 featOrth: 0.00660958135986834"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.748792135449735 bestIt: 2 CE: -0.748792135449735 featOrth: 0.00660958135986834"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.748792135449735 bestIt: 2 CE: -0.748792135449735 featOrth: 0.00660958135986834"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.748792135449735 bestIt: 2 CE: -0.748792135449735 featOrth: 0.00660958135986834"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.748792135449735 bestIt: 2 CE: -0.748627662869218 featOrth: 0.00619530459258346"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "100"       "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.244409517106167 bestIt: 1 CE: 0.244409517106167 featOrth: 3.8954787373597e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.185400474439253 bestIt: 2 CE: 0.185400474439253 featOrth: 3.04328497675926e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.164372672362123 bestIt: 3 CE: 0.164372672362123 featOrth: 6.78359361016419e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.134332348630817 bestIt: 4 CE: 0.134332348630817 featOrth: 6.43568205177411e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.114779415206953 bestIt: 5 CE: 0.114779415206953 featOrth: 0.000124645248456748"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.108258002237338 bestIt: 6 CE: 0.108258002237338 featOrth: 0.000103865401834176"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0978399923722457 bestIt: 7 CE: 0.0978399923722456 featOrth: 0.000154487788010309"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.092730902707562 bestIt: 8 CE: 0.092730902707562 featOrth: 0.000126873336971603"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0897700915298995 bestIt: 9 CE: 0.0897700915298995 featOrth: 0.000124692440079977"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.084997649304576 bestIt: 10 CE: 0.084997649304576 featOrth: 0.000137633934919202"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0829848041463062 bestIt: 11 CE: 0.0829848041463062 featOrth: 0.000133143296155386"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0808115285878685 bestIt: 12 CE: 0.0808115285878685 featOrth: 0.00013319140225241"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0808115285878685 bestIt: 12 CE: 0.0808115285878685 featOrth: 0.00013319140225241"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0744092749858592 bestIt: 14 CE: 0.0744092749858592 featOrth: 0.000164786664004297"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0725596095524975 bestIt: 15 CE: 0.0725596095524975 featOrth: 0.000164335889902654"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0725596095524975 bestIt: 15 CE: 0.0725596095524975 featOrth: 0.000164335889902654"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0711886659918525 bestIt: 17 CE: 0.0711886659918525 featOrth: 0.000163501583282696"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0711886659918525 bestIt: 17 CE: 0.0711886659918525 featOrth: 0.000163501583282696"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0711886659918525 bestIt: 17 CE: 0.0711886659918525 featOrth: 0.000163501583282696"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0711886659918525 bestIt: 17 CE: 0.0711886659918525 featOrth: 0.000163501583282696"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0711886659918525 bestIt: 17 CE: 0.0711886659918525 featOrth: 0.000163501583282696"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0678639051839652 bestIt: 22 CE: 0.0678639051839652 featOrth: 0.000200296904854955"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0664737687225152 bestIt: 23 CE: 0.0664737687225152 featOrth: 0.000203044408011055"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0620374758340213 bestIt: 24 CE: 0.0620374758340213 featOrth: 0.000169281139405133"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0495654469795617 bestIt: 25 CE: 0.0495654469795617 featOrth: 0.000138058840457648"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; i 10 ...[1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "100"       "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.36301214448911 bestIt: 1 CE: -0.36301214448911 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.415432556531959 bestIt: 2 CE: -0.415432556531959 featOrth: 0.00230899667264223"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.415432556531959 bestIt: 2 CE: -0.264067269263327 featOrth: 0.00280081372605266"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.415432556531959 bestIt: 2 CE: -0.264067269263327 featOrth: 0.00280081372605266"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.415432556531959 bestIt: 2 CE: -0.34945996365565 featOrth: 0.00307062412236973"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.43752387102329 bestIt: 6 CE: -0.43752387102329 featOrth: 0.000295539603771836"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.457062913508682 bestIt: 7 CE: -0.457062913508682 featOrth: 0.000113602380730726"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.492444492110606 bestIt: 8 CE: -0.492444492110606 featOrth: 0.000236463785642253"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.492444492110606 bestIt: 8 CE: -0.492444492110606 featOrth: 0.000236463785642253"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.6344300000994 bestIt: 10 CE: -0.6344300000994 featOrth: 0.000104540664014931"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.644830076546678 bestIt: 11 CE: -0.644830076546678 featOrth: 0.000100565085776167"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.651511490919837 bestIt: 12 CE: -0.651511490919837 featOrth: 0.000101149303441264"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.662181575459815 bestIt: 13 CE: -0.662181575459815 featOrth: 0.000103432775603137"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677544132919806 featOrth: 9.9744001214592e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677544132919806 featOrth: 9.9744001214592e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: -0.677544132919806 bestIt: 14 CE: -0.675972313912375 featOrth: 0.000129478581434189"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677514706579402 featOrth: 0.000116003319069228"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677514706579402 featOrth: 0.000116003319069228"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677514706579402 featOrth: 0.000116003319069228"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677514706579402 featOrth: 0.000116003319069228"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "100"       "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.24486466567567 bestIt: 1 CE: 0.24486466567567 featOrth: 3.8954787373597e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.182717850147193 bestIt: 2 CE: 0.182717850147193 featOrth: 4.29472005025016e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.145744097063138 bestIt: 3 CE: 0.145744097063138 featOrth: 8.61214354141716e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.125948617711368 bestIt: 4 CE: 0.125948617711368 featOrth: 6.35946272612566e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.114368634881569 bestIt: 5 CE: 0.114368634881569 featOrth: 0.000112390980124534"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.102672820738922 bestIt: 6 CE: 0.102672820738922 featOrth: 0.000110315666788085"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0900658100519336 bestIt: 7 CE: 0.0900658100519336 featOrth: 9.99359359262913e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0884597637883539 bestIt: 8 CE: 0.0884597637883539 featOrth: 7.91656850472276e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0871743231943659 bestIt: 9 CE: 0.0871743231943659 featOrth: 7.97504791397386e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.085014187157855 bestIt: 10 CE: 0.085014187157855 featOrth: 8.06313869876768e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.085014187157855 bestIt: 10 CE: 0.085014187157855 featOrth: 8.06313869876768e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.083126610822226 bestIt: 12 CE: 0.083126610822226 featOrth: 8.03542734926027e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.083126610822226 bestIt: 12 CE: 0.083126610822226 featOrth: 8.03542734926027e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.083126610822226 bestIt: 12 CE: 0.083126610822226 featOrth: 8.03542734926027e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.083126610822226 bestIt: 12 CE: 0.083126610822226 featOrth: 8.03542734926027e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0760199212099962 bestIt: 16 CE: 0.0760199212099962 featOrth: 7.98797203429841e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0636120999453672 bestIt: 17 CE: 0.0636120999453672 featOrth: 6.26224593169516e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0625789745008906 bestIt: 18 CE: 0.0625789745008906 featOrth: 6.21149699618366e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0548439543091855 bestIt: 19 CE: 0.0548439543091855 featOrth: 0.000104101756958156"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0539077681348919 bestIt: 20 CE: 0.0539077681348919 featOrth: 0.000104623573486458"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0539077681348919 bestIt: 20 CE: 0.0539077681348919 featOrth: 0.000104623573486458"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0539077681348919 bestIt: 20 CE: 0.0539077681348919 featOrth: 0.000104623573486458"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0523685652101187 bestIt: 23 CE: 0.0523685652101187 featOrth: 0.000119092206627375"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0506636365350285 bestIt: 24 CE: 0.0506636365350285 featOrth: 0.000104169307117967"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0499786330102264 bestIt: 25 CE: 0.0499786330102264 featOrth: 0.000104516236719468"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.049390348655813 bestIt: 26 CE: 0.049390348655813 featOrth: 0.000107127658482111"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0491962850379925 bestIt: 27 CE: 0.0491962850379925 featOrth: 0.000106099464279292"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0365209645288859 bestIt: 28 CE: 0.0365209645288859 featOrth: 9.26010072554305e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0365209645288859 bestIt: 28 CE: 0.0372110308330445 featOrth: 7.49208583560487e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.025844921033304 bestIt: 30 CE: 0.025844921033304 featOrth: 6.93213289015161e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0257541341257113 bestIt: 31 CE: 0.0257541341257113 featOrth: 6.94691352400177e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0256915982305088 bestIt: 32 CE: 0.0256915982305088 featOrth: 6.94405765681499e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.0256915982305088 bestIt: 32 CE: 0.0257153544105855 featOrth: 6.89356001554465e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.0256871685139165 bestIt: 34 CE: 0.0256871685139165 featOrth: 6.88997063400277e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.0256871685139165 bestIt: 34 CE: 0.0256880319739488 featOrth: 6.88500607948414e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.0256819778523346 bestIt: 36 CE: 0.0256819778523346 featOrth: 6.88299554808542e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.0256751691449959 bestIt: 37 CE: 0.0256751691449959 featOrth: 6.88132882349444e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.0256699945808138 bestIt: 38 CE: 0.0256699945808138 featOrth: 6.88130691423606e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 39 bestEv: 0.0256660107125178 bestIt: 39 CE: 0.0256660107125178 featOrth: 6.88311704984994e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 40 bestEv: 0.0256660107125178 bestIt: 39 CE: 0.0256661950745787 featOrth: 6.8878780331478e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 41 bestEv: 0.0256660107125178 bestIt: 39 CE: 0.0256668269240548 featOrth: 6.89349439283567e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 42 bestEv: 0.0256660107125178 bestIt: 39 CE: 0.025670811380993 featOrth: 6.89967213939373e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 43 bestEv: 0.024193222401332 bestIt: 43 CE: 0.024193222401332 featOrth: 7.92677526933941e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 44 bestEv: 0.024193222401332 bestIt: 43 CE: 0.024193222401332 featOrth: 7.92677526933941e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 45 bestEv: 0.024193222401332 bestIt: 43 CE: 0.024193222401332 featOrth: 7.92677526933941e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 46 bestEv: 0.024193222401332 bestIt: 43 CE: 0.024193222401332 featOrth: 7.92677526933941e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 47 bestEv: 0.0199776702142631 bestIt: 47 CE: 0.0199776702142631 featOrth: 3.35472834465409e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 48 bestEv: 0.0199776702142631 bestIt: 47 CE: 0.0199776702142631 featOrth: 3.35472834465409e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 49 bestEv: 0.0184784960355138 bestIt: 49 CE: 0.0184784960355138 featOrth: 2.68597043910107e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 50 bestEv: 0.0175685977633998 bestIt: 50 CE: 0.0175685977633998 featOrth: 2.91992648054329e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 51 bestEv: 0.0159676333939732 bestIt: 51 CE: 0.0159676333939732 featOrth: 2.8927040661509e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 52 bestEv: 0.015457027781871 bestIt: 52 CE: 0.015457027781871 featOrth: 2.81243134975398e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 53 bestEv: 0.0148509870891125 bestIt: 53 CE: 0.0148509870891125 featOrth: 2.74365175848296e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 54 bestEv: 0.0148509870891125 bestIt: 53 CE: 0.0149939130012451 featOrth: 2.82137995217236e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 55 bestEv: 0.0137719591377578 bestIt: 55 CE: 0.0137719591377578 featOrth: 2.90510862238909e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 56 bestEv: 0.0137719591377578 bestIt: 55 CE: 0.014765567025075 featOrth: 3.07548580706123e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 57 bestEv: 0.0133178124118065 bestIt: 57 CE: 0.0133178124118065 featOrth: 3.20048515741801e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 58 bestEv: 0.0133178124118065 bestIt: 57 CE: 0.0135175323117845 featOrth: 1.91838024234639e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 59 bestEv: 0.0124026441007662 bestIt: 59 CE: 0.0124026441007662 featOrth: 2.55646584088978e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 60 bestEv: 0.0124026441007662 bestIt: 59 CE: 0.0131796421513681 featOrth: 1.75828975582729e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 61 bestEv: 0.0124026441007662 bestIt: 59 CE: 0.0126857066851048 featOrth: 1.7727248022955e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 62 bestEv: 0.0124026441007662 bestIt: 59 CE: 0.0124616191683095 featOrth: 1.83551942101204e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 63 bestEv: 0.0123977683840545 bestIt: 63 CE: 0.0123977683840545 featOrth: 1.86184420825257e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 64 bestEv: 0.0123518868605569 bestIt: 64 CE: 0.0123518868605569 featOrth: 1.8306586572854e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 65 bestEv: 0.0123038488480845 bestIt: 65 CE: 0.0123038488480845 featOrth: 1.80031470791419e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 66 bestEv: 0.0122114682526529 bestIt: 66 CE: 0.0122114682526529 featOrth: 1.74958709630447e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 67 bestEv: 0.012177449611871 bestIt: 67 CE: 0.012177449611871 featOrth: 1.73549378333063e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 68 bestEv: 0.0121222828163378 bestIt: 68 CE: 0.0121222828163378 featOrth: 1.70953388774691e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 69 bestEv: 0.0120457905725344 bestIt: 69 CE: 0.0120457905725344 featOrth: 1.65724293212836e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 70 bestEv: 0.0120457905725344 bestIt: 69 CE: 0.012046102347245 featOrth: 1.62703703001159e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 71 bestEv: 0.0120139866942594 bestIt: 71 CE: 0.0120139866942594 featOrth: 1.62220375151908e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 72 bestEv: 0.011991527063442 bestIt: 72 CE: 0.011991527063442 featOrth: 1.60331968272925e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 73 bestEv: 0.0119750103607104 bestIt: 73 CE: 0.0119750103607104 featOrth: 1.59096892635289e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 74 bestEv: 0.0119625801282645 bestIt: 74 CE: 0.0119625801282645 featOrth: 1.58048474539021e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 75 bestEv: 0.0119625801282645 bestIt: 74 CE: 0.0119657530640919 featOrth: 1.57631003042604e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 76 bestEv: 0.0119625801282645 bestIt: 74 CE: 0.0119657530640919 featOrth: 1.57631003042604e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 77 bestEv: 0.0119399580289998 bestIt: 77 CE: 0.0119399580289998 featOrth: 1.55713724841557e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 78 bestEv: 0.0119399580289998 bestIt: 77 CE: 0.0119434990629917 featOrth: 1.55651148652041e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 79 bestEv: 0.0119201387767789 bestIt: 79 CE: 0.0119201387767789 featOrth: 1.54395337229384e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 80 bestEv: 0.0119145154402753 bestIt: 80 CE: 0.0119145154402753 featOrth: 1.54971650202435e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 81 bestEv: 0.0119145154402753 bestIt: 80 CE: 0.0119226909963201 featOrth: 1.55132961181815e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 82 bestEv: 0.0119145154402753 bestIt: 80 CE: 0.0119157376174851 featOrth: 1.55024027743453e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 83 bestEv: 0.0119125931150639 bestIt: 83 CE: 0.0119125931150639 featOrth: 1.55097618183952e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 84 bestEv: 0.01188921955483 bestIt: 84 CE: 0.01188921955483 featOrth: 1.53920765151486e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 85 bestEv: 0.0118833763127743 bestIt: 85 CE: 0.0118833763127743 featOrth: 1.5373126750282e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 86 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118799862457062 featOrth: 1.53498240765117e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 87 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118844368880504 featOrth: 1.53276262794725e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 88 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118858314888712 featOrth: 1.5310175667824e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 89 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118858314888712 featOrth: 1.5310175667824e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 90 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118858314888712 featOrth: 1.5310175667824e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 91 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118858314888712 featOrth: 1.5310175667824e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 92 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118858314888712 featOrth: 1.5310175667824e-05"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "100"       "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "100"       "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.244409517106167 bestIt: 1 CE: 0.244409517106167 featOrth: 3.8954787373597e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.185400474439253 bestIt: 2 CE: 0.185400474439253 featOrth: 3.04328497675926e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.164372672362123 bestIt: 3 CE: 0.164372672362123 featOrth: 6.78359361016419e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.134332348630817 bestIt: 4 CE: 0.134332348630817 featOrth: 6.43568205177411e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.114779415206953 bestIt: 5 CE: 0.114779415206953 featOrth: 0.000124645248456748"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.108258002237338 bestIt: 6 CE: 0.108258002237338 featOrth: 0.000103865401834176"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0978399923722457 bestIt: 7 CE: 0.0978399923722456 featOrth: 0.000154487788010309"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.092730902707562 bestIt: 8 CE: 0.092730902707562 featOrth: 0.000126873336971603"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0897700915298995 bestIt: 9 CE: 0.0897700915298995 featOrth: 0.000124692440079977"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.084997649304576 bestIt: 10 CE: 0.084997649304576 featOrth: 0.000137633934919202"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0829848041463062 bestIt: 11 CE: 0.0829848041463062 featOrth: 0.000133143296155386"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0808115285878685 bestIt: 12 CE: 0.0808115285878685 featOrth: 0.00013319140225241"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0808115285878685 bestIt: 12 CE: 0.0808115285878685 featOrth: 0.00013319140225241"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0744092749858592 bestIt: 14 CE: 0.0744092749858592 featOrth: 0.000164786664004297"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0725596095524975 bestIt: 15 CE: 0.0725596095524975 featOrth: 0.000164335889902654"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0725596095524975 bestIt: 15 CE: 0.0725596095524975 featOrth: 0.000164335889902654"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0711886659918525 bestIt: 17 CE: 0.0711886659918525 featOrth: 0.000163501583282696"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0711886659918525 bestIt: 17 CE: 0.0711886659918525 featOrth: 0.000163501583282696"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0711886659918525 bestIt: 17 CE: 0.0711886659918525 featOrth: 0.000163501583282696"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0711886659918525 bestIt: 17 CE: 0.0711886659918525 featOrth: 0.000163501583282696"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0711886659918525 bestIt: 17 CE: 0.0711886659918525 featOrth: 0.000163501583282696"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0678639051839652 bestIt: 22 CE: 0.0678639051839652 featOrth: 0.000200296904854955"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0664737687225152 bestIt: 23 CE: 0.0664737687225152 featOrth: 0.000203044408011055"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0620374758340213 bestIt: 24 CE: 0.0620374758340213 featOrth: 0.000169281139405133"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0495654469795617 bestIt: 25 CE: 0.0495654469795617 featOrth: 0.000138058840457648"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0494338093074407 bestIt: 26 CE: 0.0494338093074407 featOrth: 0.00013565961800081"</span></span>
 <span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
 <span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "100"       "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.36301214448911 bestIt: 1 CE: -0.36301214448911 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.415432556531959 bestIt: 2 CE: -0.415432556531959 featOrth: 0.00230899667264223"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.415432556531959 bestIt: 2 CE: -0.264067269263327 featOrth: 0.00280081372605266"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.415432556531959 bestIt: 2 CE: -0.264067269263327 featOrth: 0.00280081372605266"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.415432556531959 bestIt: 2 CE: -0.34945996365565 featOrth: 0.00307062412236973"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.43752387102329 bestIt: 6 CE: -0.43752387102329 featOrth: 0.000295539603771836"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.457062913508682 bestIt: 7 CE: -0.457062913508682 featOrth: 0.000113602380730726"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.492444492110606 bestIt: 8 CE: -0.492444492110606 featOrth: 0.000236463785642253"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.492444492110606 bestIt: 8 CE: -0.492444492110606 featOrth: 0.000236463785642253"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.6344300000994 bestIt: 10 CE: -0.6344300000994 featOrth: 0.000104540664014931"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.644830076546678 bestIt: 11 CE: -0.644830076546678 featOrth: 0.000100565085776167"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.651511490919837 bestIt: 12 CE: -0.651511490919837 featOrth: 0.000101149303441264"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.662181575459815 bestIt: 13 CE: -0.662181575459815 featOrth: 0.000103432775603137"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677544132919806 featOrth: 9.9744001214592e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677544132919806 featOrth: 9.9744001214592e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: -0.677544132919806 bestIt: 14 CE: -0.675972313912375 featOrth: 0.000129478581434189"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677514706579402 featOrth: 0.000116003319069228"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677514706579402 featOrth: 0.000116003319069228"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677514706579402 featOrth: 0.000116003319069228"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: -0.677544132919806 bestIt: 14 CE: -0.677514706579402 featOrth: 0.000116003319069228"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
 <span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "100"       "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.24486466567567 bestIt: 1 CE: 0.24486466567567 featOrth: 3.8954787373597e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.182717850147193 bestIt: 2 CE: 0.182717850147193 featOrth: 4.29472005025016e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.145744097063138 bestIt: 3 CE: 0.145744097063138 featOrth: 8.61214354141716e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.125948617711368 bestIt: 4 CE: 0.125948617711368 featOrth: 6.35946272612566e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.114368634881569 bestIt: 5 CE: 0.114368634881569 featOrth: 0.000112390980124534"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.102672820738922 bestIt: 6 CE: 0.102672820738922 featOrth: 0.000110315666788085"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0900658100519336 bestIt: 7 CE: 0.0900658100519336 featOrth: 9.99359359262913e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0884597637883539 bestIt: 8 CE: 0.0884597637883539 featOrth: 7.91656850472276e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0871743231943659 bestIt: 9 CE: 0.0871743231943659 featOrth: 7.97504791397386e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.085014187157855 bestIt: 10 CE: 0.085014187157855 featOrth: 8.06313869876768e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.085014187157855 bestIt: 10 CE: 0.085014187157855 featOrth: 8.06313869876768e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.083126610822226 bestIt: 12 CE: 0.083126610822226 featOrth: 8.03542734926027e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.083126610822226 bestIt: 12 CE: 0.083126610822226 featOrth: 8.03542734926027e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.083126610822226 bestIt: 12 CE: 0.083126610822226 featOrth: 8.03542734926027e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.083126610822226 bestIt: 12 CE: 0.083126610822226 featOrth: 8.03542734926027e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0760199212099962 bestIt: 16 CE: 0.0760199212099962 featOrth: 7.98797203429841e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0636120999453672 bestIt: 17 CE: 0.0636120999453672 featOrth: 6.26224593169516e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0625789745008906 bestIt: 18 CE: 0.0625789745008906 featOrth: 6.21149699618366e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0548439543091855 bestIt: 19 CE: 0.0548439543091855 featOrth: 0.000104101756958156"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0539077681348919 bestIt: 20 CE: 0.0539077681348919 featOrth: 0.000104623573486458"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0539077681348919 bestIt: 20 CE: 0.0539077681348919 featOrth: 0.000104623573486458"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0539077681348919 bestIt: 20 CE: 0.0539077681348919 featOrth: 0.000104623573486458"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0523685652101187 bestIt: 23 CE: 0.0523685652101187 featOrth: 0.000119092206627375"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0506636365350285 bestIt: 24 CE: 0.0506636365350285 featOrth: 0.000104169307117967"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0499786330102264 bestIt: 25 CE: 0.0499786330102264 featOrth: 0.000104516236719468"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.049390348655813 bestIt: 26 CE: 0.049390348655813 featOrth: 0.000107127658482111"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0491962850379925 bestIt: 27 CE: 0.0491962850379925 featOrth: 0.000106099464279292"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0365209645288859 bestIt: 28 CE: 0.0365209645288859 featOrth: 9.26010072554305e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0365209645288859 bestIt: 28 CE: 0.0372110308330445 featOrth: 7.49208583560487e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.025844921033304 bestIt: 30 CE: 0.025844921033304 featOrth: 6.93213289015161e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0257541341257113 bestIt: 31 CE: 0.0257541341257113 featOrth: 6.94691352400177e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0256915982305088 bestIt: 32 CE: 0.0256915982305088 featOrth: 6.94405765681499e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.0256915982305088 bestIt: 32 CE: 0.0257153544105855 featOrth: 6.89356001554465e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.0256871685139165 bestIt: 34 CE: 0.0256871685139165 featOrth: 6.88997063400277e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.0256871685139165 bestIt: 34 CE: 0.0256880319739488 featOrth: 6.88500607948414e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.0256819778523346 bestIt: 36 CE: 0.0256819778523346 featOrth: 6.88299554808542e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.0256751691449959 bestIt: 37 CE: 0.0256751691449959 featOrth: 6.88132882349444e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.0256699945808138 bestIt: 38 CE: 0.0256699945808138 featOrth: 6.88130691423606e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 39 bestEv: 0.0256660107125178 bestIt: 39 CE: 0.0256660107125178 featOrth: 6.88311704984994e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 40 bestEv: 0.0256660107125178 bestIt: 39 CE: 0.0256661950745787 featOrth: 6.8878780331478e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 41 bestEv: 0.0256660107125178 bestIt: 39 CE: 0.0256668269240548 featOrth: 6.89349439283567e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 42 bestEv: 0.0256660107125178 bestIt: 39 CE: 0.025670811380993 featOrth: 6.89967213939373e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 43 bestEv: 0.024193222401332 bestIt: 43 CE: 0.024193222401332 featOrth: 7.92677526933941e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 44 bestEv: 0.024193222401332 bestIt: 43 CE: 0.024193222401332 featOrth: 7.92677526933941e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 45 bestEv: 0.024193222401332 bestIt: 43 CE: 0.024193222401332 featOrth: 7.92677526933941e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 46 bestEv: 0.024193222401332 bestIt: 43 CE: 0.024193222401332 featOrth: 7.92677526933941e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 47 bestEv: 0.0199776702142631 bestIt: 47 CE: 0.0199776702142631 featOrth: 3.35472834465409e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 48 bestEv: 0.0199776702142631 bestIt: 47 CE: 0.0199776702142631 featOrth: 3.35472834465409e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 49 bestEv: 0.0184784960355138 bestIt: 49 CE: 0.0184784960355138 featOrth: 2.68597043910107e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 50 bestEv: 0.0175685977633998 bestIt: 50 CE: 0.0175685977633998 featOrth: 2.91992648054329e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 51 bestEv: 0.0159676333939732 bestIt: 51 CE: 0.0159676333939732 featOrth: 2.8927040661509e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 52 bestEv: 0.015457027781871 bestIt: 52 CE: 0.015457027781871 featOrth: 2.81243134975398e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 53 bestEv: 0.0148509870891125 bestIt: 53 CE: 0.0148509870891125 featOrth: 2.74365175848296e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 54 bestEv: 0.0148509870891125 bestIt: 53 CE: 0.0149939130012451 featOrth: 2.82137995217236e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 55 bestEv: 0.0137719591377578 bestIt: 55 CE: 0.0137719591377578 featOrth: 2.90510862238909e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 56 bestEv: 0.0137719591377578 bestIt: 55 CE: 0.014765567025075 featOrth: 3.07548580706123e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 57 bestEv: 0.0133178124118065 bestIt: 57 CE: 0.0133178124118065 featOrth: 3.20048515741801e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 58 bestEv: 0.0133178124118065 bestIt: 57 CE: 0.0135175323117845 featOrth: 1.91838024234639e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 59 bestEv: 0.0124026441007662 bestIt: 59 CE: 0.0124026441007662 featOrth: 2.55646584088978e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 60 bestEv: 0.0124026441007662 bestIt: 59 CE: 0.0131796421513681 featOrth: 1.75828975582729e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 61 bestEv: 0.0124026441007662 bestIt: 59 CE: 0.0126857066851048 featOrth: 1.7727248022955e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 62 bestEv: 0.0124026441007662 bestIt: 59 CE: 0.0124616191683095 featOrth: 1.83551942101204e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 63 bestEv: 0.0123977683840545 bestIt: 63 CE: 0.0123977683840545 featOrth: 1.86184420825257e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 64 bestEv: 0.0123518868605569 bestIt: 64 CE: 0.0123518868605569 featOrth: 1.8306586572854e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 65 bestEv: 0.0123038488480845 bestIt: 65 CE: 0.0123038488480845 featOrth: 1.80031470791419e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 66 bestEv: 0.0122114682526529 bestIt: 66 CE: 0.0122114682526529 featOrth: 1.74958709630447e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 67 bestEv: 0.012177449611871 bestIt: 67 CE: 0.012177449611871 featOrth: 1.73549378333063e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 68 bestEv: 0.0121222828163378 bestIt: 68 CE: 0.0121222828163378 featOrth: 1.70953388774691e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 69 bestEv: 0.0120457905725344 bestIt: 69 CE: 0.0120457905725344 featOrth: 1.65724293212836e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 70 bestEv: 0.0120457905725344 bestIt: 69 CE: 0.012046102347245 featOrth: 1.62703703001159e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 71 bestEv: 0.0120139866942594 bestIt: 71 CE: 0.0120139866942594 featOrth: 1.62220375151908e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 72 bestEv: 0.011991527063442 bestIt: 72 CE: 0.011991527063442 featOrth: 1.60331968272925e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 73 bestEv: 0.0119750103607104 bestIt: 73 CE: 0.0119750103607104 featOrth: 1.59096892635289e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 74 bestEv: 0.0119625801282645 bestIt: 74 CE: 0.0119625801282645 featOrth: 1.58048474539021e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 75 bestEv: 0.0119625801282645 bestIt: 74 CE: 0.0119657530640919 featOrth: 1.57631003042604e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 76 bestEv: 0.0119625801282645 bestIt: 74 CE: 0.0119657530640919 featOrth: 1.57631003042604e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 77 bestEv: 0.0119399580289998 bestIt: 77 CE: 0.0119399580289998 featOrth: 1.55713724841557e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 78 bestEv: 0.0119399580289998 bestIt: 77 CE: 0.0119434990629917 featOrth: 1.55651148652041e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 79 bestEv: 0.0119201387767789 bestIt: 79 CE: 0.0119201387767789 featOrth: 1.54395337229384e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 80 bestEv: 0.0119145154402753 bestIt: 80 CE: 0.0119145154402753 featOrth: 1.54971650202435e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 81 bestEv: 0.0119145154402753 bestIt: 80 CE: 0.0119226909963201 featOrth: 1.55132961181815e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 82 bestEv: 0.0119145154402753 bestIt: 80 CE: 0.0119157376174851 featOrth: 1.55024027743453e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 83 bestEv: 0.0119125931150639 bestIt: 83 CE: 0.0119125931150639 featOrth: 1.55097618183952e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 84 bestEv: 0.01188921955483 bestIt: 84 CE: 0.01188921955483 featOrth: 1.53920765151486e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 85 bestEv: 0.0118833763127743 bestIt: 85 CE: 0.0118833763127743 featOrth: 1.5373126750282e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 86 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118799862457062 featOrth: 1.53498240765117e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 87 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118844368880504 featOrth: 1.53276262794725e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 88 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118858314888712 featOrth: 1.5310175667824e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 89 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118858314888712 featOrth: 1.5310175667824e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 90 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118858314888712 featOrth: 1.5310175667824e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 91 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118858314888712 featOrth: 1.5310175667824e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 92 bestEv: 0.0118799862457062 bestIt: 86 CE: 0.0118858314888712 featOrth: 1.5310175667824e-05"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "100"       "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.498426139658693 bestIt: 1 CE: -0.498426139658693 featOrth: 0.00231377941384869"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
 <span><span class="co">#&gt; [1] "Grassmannx1x1"</span></span>
 <span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
 <span><span class="co">#&gt; [1] 0.99</span></span>
@@ -722,45 +1351,162 @@ <h3 id="evaluating-machine-learning-objective-functions">Evaluating Machine Lear
 <span><span class="co">#&gt; [1] "lineSearch"</span></span>
 <span><span class="co">#&gt; [1] "Grassmann" "1"         "1"        </span></span>
 <span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
-<span><span class="co">#&gt; [1] "initialDataTerm: -0.857027012460654  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.568063748955966 bestIt: 1 CE: -0.568063748955966"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.6384098624039 bestIt: 2 CE: -0.6384098624039"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.821032892373937 bestIt: 3 CE: -0.821032892373937"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.853348011551356 bestIt: 4 CE: -0.853348011551356"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.853348011551356 bestIt: 4 CE: -0.853348011551356"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.853348011551356 bestIt: 4 CE: -0.8334722954351"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.853348011551356 bestIt: 4 CE: -0.827310232364803"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.853348011551356 bestIt: 4 CE: -0.826230051515903"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.853348011551356 bestIt: 4 CE: -0.784256680859058"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.859872695845605 bestIt: 10 CE: -0.859872695845605"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.859872695845605 bestIt: 10 CE: -0.859872695845605"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.859872695845605 bestIt: 10 CE: -0.859872695845605"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.859872695845605 bestIt: 10 CE: -0.857867514510308"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.859872695845605 bestIt: 10 CE: -0.857867514510308"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.859872695845605 bestIt: 10 CE: -0.857867514510308"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: -0.859872695845605 bestIt: 10 CE: -0.857867514510308"</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 0.650158753645586  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.236569233766486 bestIt: 1 CE: 0.236569233766486 featOrth: 0.00512043927990967"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.112569804039395 bestIt: 2 CE: 0.112569804039395 featOrth: 0.00819400566924728"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.061713891941157 bestIt: 3 CE: 0.061713891941157 featOrth: 0.00483432045175019"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.0472544706931552 bestIt: 4 CE: 0.0472544706931552 featOrth: 0.00140646076579307"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.0378303138846951 bestIt: 5 CE: 0.0378303138846951 featOrth: 0.00114437969472609"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.0308712446189825 bestIt: 6 CE: 0.0308712446189825 featOrth: 0.00238430431041012"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0278371987361591 bestIt: 7 CE: 0.0278371987361591 featOrth: 0.000898250194674604"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0230756810913965 bestIt: 8 CE: 0.0230756810913965 featOrth: 0.00100413542788787"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0212982633441387 bestIt: 9 CE: 0.0212982633441387 featOrth: 0.000975689110818281"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.019333863075991 bestIt: 10 CE: 0.019333863075991 featOrth: 0.000471901740918"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0174921534310822 bestIt: 11 CE: 0.0174921534310822 featOrth: 0.000954745077002844"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0158417176764093 bestIt: 12 CE: 0.0158417176764093 featOrth: 0.000193714588965449"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0146243383189442 bestIt: 13 CE: 0.0146243383189442 featOrth: 0.000644467614081938"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0136737450234315 bestIt: 14 CE: 0.0136737450234315 featOrth: 0.000130009336489093"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0127556025901414 bestIt: 15 CE: 0.0127556025901414 featOrth: 0.000441934087363103"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0120775761535138 bestIt: 16 CE: 0.0120775761535138 featOrth: 5.67218144416688e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0114116727552303 bestIt: 17 CE: 0.0114116727552303 featOrth: 0.000179227768590719"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0109577296277224 bestIt: 18 CE: 0.0109577296277224 featOrth: 4.26169783059304e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0102607802336552 bestIt: 19 CE: 0.0102607802336552 featOrth: 0.000200275215791469"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0100047819406394 bestIt: 20 CE: 0.0100047819406394 featOrth: 7.20599562531889e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.00982485480320524 bestIt: 21 CE: 0.00982485480320524 featOrth: 2.92910037114749e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.00964445196788564 bestIt: 22 CE: 0.00964445196788564 featOrth: 5.97434419582065e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.00964445196788564 bestIt: 22 CE: 0.010063140825853 featOrth: 4.93686665614018e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.00964445196788564 bestIt: 22 CE: 0.010063140825853 featOrth: 4.93686665614018e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.00964445196788564 bestIt: 22 CE: 0.010063140825853 featOrth: 4.93686665614018e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.00964445196788564 bestIt: 22 CE: 0.0100467684135958 featOrth: 2.29166701175529e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.00928565607789682 bestIt: 27 CE: 0.00928565607789682 featOrth: 1.72261095105127e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.00916976403747019 bestIt: 28 CE: 0.00916976403747019 featOrth: 2.69960810779848e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.00910414661015344 bestIt: 29 CE: 0.00910414661015344 featOrth: 2.69786499862247e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.00900059437457172 bestIt: 30 CE: 0.00900059437457172 featOrth: 2.18536871755165e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.00892008516364639 bestIt: 31 CE: 0.00892008516364639 featOrth: 1.56632545651466e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.00878190083371231 bestIt: 32 CE: 0.00878190083371231 featOrth: 1.48075294548143e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.00878190083371231 bestIt: 32 CE: 0.0090469779707051 featOrth: 1.59932118112098e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.00878190083371231 bestIt: 32 CE: 0.00902778061917959 featOrth: 1.59387791279553e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.00878190083371231 bestIt: 32 CE: 0.00902046017559822 featOrth: 1.60595211649962e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.00878190083371231 bestIt: 32 CE: 0.0089813093836551 featOrth: 1.53542571923644e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.00878190083371231 bestIt: 32 CE: 0.00898637781073108 featOrth: 1.54660623076691e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.00878190083371231 bestIt: 32 CE: 0.0087875126726722 featOrth: 1.51961754365706e-05"</span></span>
 <span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
 <span><span class="co">#&gt; [1] "cca"</span></span>
-<span><span class="co">#&gt; [1] "pca"</span></span>
-<span><span class="co">#&gt; [1] "Grassmannx0.1x0.1"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx1x1"</span></span>
 <span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
 <span><span class="co">#&gt; [1] 0.99</span></span>
 <span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
 <span><span class="co">#&gt; [1] "lineSearch"</span></span>
-<span><span class="co">#&gt; [1] "Grassmann" "0.1"       "0.1"      </span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "1"         "1"        </span></span>
 <span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
-<span><span class="co">#&gt; [1] "initialDataTerm: -0.917111645375717  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.395328252193667 bestIt: 1 CE: -0.395328252193667"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.876505321910793 bestIt: 2 CE: -0.876505321910793"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.876505321910793 bestIt: 2 CE: -0.715775124305709"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.876505321910793 bestIt: 2 CE: -0.556572105988905"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.876505321910793 bestIt: 2 CE: -0.704977394581536"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.876505321910793 bestIt: 2 CE: -0.701747921610733"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.876505321910793 bestIt: 2 CE: -0.701644867438938"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.876505321910793 bestIt: 2 CE: -0.712268348974026"</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.857027012460654  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.484669112121528 bestIt: 1 CE: -0.484669112121528 featOrth: 0.116412143087396"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.484669112121527 bestIt: 1 CE: -0.419128088217896 featOrth: 0.1023494268179"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.875840288748677 bestIt: 3 CE: -0.875840288748677 featOrth: 0.0139109578546765"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.87961607587513 bestIt: 4 CE: -0.87961607587513 featOrth: 0.0152531637863663"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.922794655190393 bestIt: 5 CE: -0.922794655190393 featOrth: 0.0121746042697442"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.929963662013183 bestIt: 6 CE: -0.929963662013183 featOrth: 0.00851301356880547"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.933592981845909 bestIt: 7 CE: -0.933592981845909 featOrth: 0.011672442559449"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.933592981845909 bestIt: 7 CE: -0.928181053368062 featOrth: 0.0108426260974901"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.933592981845909 bestIt: 7 CE: -0.922033763955916 featOrth: 0.0104305144463107"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.933592981845909 bestIt: 7 CE: -0.882087696489809 featOrth: 0.0106019835916773"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.933592981845909 bestIt: 7 CE: -0.872145451258704 featOrth: 0.0103913398339846"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.933592981845909 bestIt: 7 CE: -0.872145451258704 featOrth: 0.0103913398339846"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.933592981845909 bestIt: 7 CE: -0.877737312632469 featOrth: 0.0121101340949887"</span></span>
 <span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx1x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "1"         "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 0.650158753645586  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.233297749695571 bestIt: 1 CE: 0.233297749695571 featOrth: 0.00512043927990967"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.111451066848263 bestIt: 2 CE: 0.111451066848263 featOrth: 0.0156701267504654"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.071182486580532 bestIt: 3 CE: 0.071182486580532 featOrth: 0.00126630874381214"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.0471908774303602 bestIt: 4 CE: 0.0471908774303602 featOrth: 0.00236731951199521"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.0368152098864028 bestIt: 5 CE: 0.0368152098864028 featOrth: 0.00287956844794434"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.0327903561857563 bestIt: 6 CE: 0.0327903561857563 featOrth: 0.000595255091961607"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.02756912211316 bestIt: 7 CE: 0.02756912211316 featOrth: 0.00162708967756669"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0248221957549467 bestIt: 8 CE: 0.0248221957549467 featOrth: 0.000910919496307325"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0215278965209146 bestIt: 9 CE: 0.0215278965209146 featOrth: 0.00188567171675998"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0197002455081917 bestIt: 10 CE: 0.0197002455081917 featOrth: 0.00034399922521466"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0159830090668117 bestIt: 11 CE: 0.0159830090668117 featOrth: 0.00122564147769768"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0159830090668117 bestIt: 11 CE: 0.0168256276754948 featOrth: 0.000114609203620223"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0138499086005959 bestIt: 13 CE: 0.0138499086005959 featOrth: 0.000302936844719299"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0126025101604506 bestIt: 14 CE: 0.0126025101604506 featOrth: 0.000632135811173528"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0120412797010871 bestIt: 15 CE: 0.0120412797010871 featOrth: 9.90590448693642e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0118247244109087 bestIt: 16 CE: 0.0118247244109087 featOrth: 0.000199270066257349"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0115719347763237 bestIt: 17 CE: 0.0115719347763237 featOrth: 5.73621313390431e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0114266038640231 bestIt: 18 CE: 0.0114266038640231 featOrth: 0.00013894372887345"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0108018583299693 bestIt: 19 CE: 0.0108018583299693 featOrth: 0.00024693823272772"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0104958266117168 bestIt: 20 CE: 0.0104958266117168 featOrth: 0.000219369035833475"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0103414072869726 bestIt: 21 CE: 0.0103414072869726 featOrth: 0.000166386828119625"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0103074519807408 bestIt: 22 CE: 0.0103074519807408 featOrth: 0.000173798944960884"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0102631999526572 bestIt: 23 CE: 0.0102631999526572 featOrth: 0.000175766506645848"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0102122557645351 bestIt: 24 CE: 0.0102122557645351 featOrth: 0.000173527561549529"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.00999794103935 bestIt: 25 CE: 0.00999794103935 featOrth: 7.31924045979468e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.00977843861001831 bestIt: 26 CE: 0.00977843861001831 featOrth: 0.00011288173571374"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.00960175716802986 bestIt: 27 CE: 0.00960175716802986 featOrth: 0.000129291929029333"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.00945316068446364 bestIt: 28 CE: 0.00945316068446364 featOrth: 6.613579378929e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.00943609637371024 bestIt: 29 CE: 0.00943609637371024 featOrth: 6.97631696480906e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.00929603685176095 bestIt: 30 CE: 0.00929603685176095 featOrth: 0.000110480442094461"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.00917268890027692 bestIt: 31 CE: 0.00917268890027692 featOrth: 4.86460805423769e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0090900911668836 bestIt: 32 CE: 0.0090900911668836 featOrth: 9.27926871294868e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.00899257820911672 bestIt: 33 CE: 0.00899257820911672 featOrth: 4.79371762943166e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.00892763956921303 bestIt: 34 CE: 0.00892763956921303 featOrth: 4.93432725942198e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.00886295370148408 bestIt: 35 CE: 0.00886295370148408 featOrth: 4.15317236282846e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.00866829814328137 bestIt: 36 CE: 0.00866829814328137 featOrth: 3.36827341143808e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.0086422288300812 bestIt: 37 CE: 0.0086422288300812 featOrth: 4.02990994734148e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.00861634705525822 bestIt: 38 CE: 0.00861634705525822 featOrth: 4.00707724111419e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 39 bestEv: 0.00861634705525822 bestIt: 38 CE: 0.00865996349694209 featOrth: 2.9376354855588e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 40 bestEv: 0.00861634705525822 bestIt: 38 CE: 0.00866921626058228 featOrth: 3.35810213170963e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 41 bestEv: 0.00861634705525822 bestIt: 38 CE: 0.00864953431897996 featOrth: 3.1918942266953e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 42 bestEv: 0.00861634705525822 bestIt: 38 CE: 0.00862949071235637 featOrth: 3.1302998880662e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 43 bestEv: 0.0086117619745801 bestIt: 43 CE: 0.0086117619745801 featOrth: 3.09670563858821e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 44 bestEv: 0.00859264795518559 bestIt: 44 CE: 0.00859264795518559 featOrth: 2.25134306390542e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 45 bestEv: 0.00857783741904401 bestIt: 45 CE: 0.00857783741904401 featOrth: 2.22114410608385e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 46 bestEv: 0.00857783741904401 bestIt: 45 CE: 0.00857783741904401 featOrth: 2.22114410608385e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 47 bestEv: 0.00857783741904401 bestIt: 45 CE: 0.00857783741904401 featOrth: 2.22114410608385e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 48 bestEv: 0.00857783741904401 bestIt: 45 CE: 0.00857783741904401 featOrth: 2.22114410608385e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 49 bestEv: 0.00857783741904401 bestIt: 45 CE: 0.00857783741904401 featOrth: 2.22114410608385e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 50 bestEv: 0.00857783741904401 bestIt: 45 CE: 0.00857783741904401 featOrth: 2.22114410608385e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 51 bestEv: 0.0085437177148271 bestIt: 51 CE: 0.0085437177148271 featOrth: 2.3097522685974e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 52 bestEv: 0.00852836361816449 bestIt: 52 CE: 0.00852836361816449 featOrth: 1.79239543288373e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 53 bestEv: 0.00852836361816449 bestIt: 52 CE: 0.00855543575843603 featOrth: 1.78583181486103e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 54 bestEv: 0.00852836361816449 bestIt: 52 CE: 0.00863561976147224 featOrth: 1.79001571924121e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 55 bestEv: 0.00852836361816449 bestIt: 52 CE: 0.00904338172767964 featOrth: 1.78715477651634e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 56 bestEv: 0.00852836361816449 bestIt: 52 CE: 0.0094536644914835 featOrth: 1.8028211353587e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 57 bestEv: 0.00852836361816449 bestIt: 52 CE: 0.00892689398844575 featOrth: 1.80164428204242e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 58 bestEv: 0.00852836361816449 bestIt: 52 CE: 0.0091874883636805 featOrth: 4.9582064556597e-05"</span></span>
+<span><span class="co">#&gt; i 20 ...[1] "robust"         "centerAndScale" "np"            </span></span>
 <span><span class="co">#&gt; [1] "cca"</span></span>
 <span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Grassmannx1x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Grassmann" "1"         "1"        </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.857027012460654  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.387314186394538 bestIt: 1 CE: -0.387314186394538 featOrth: 0.116412143087396"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.674870749704496 bestIt: 2 CE: -0.674870749704496 featOrth: 0.00642088397670395"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.674870749704496 bestIt: 2 CE: -0.487137584237176 featOrth: 0.0682626403670032"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.870000491549228 bestIt: 4 CE: -0.870000491549228 featOrth: 0.035867020333976"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.870000491549228 bestIt: 4 CE: -0.870000491549228 featOrth: 0.035867020333976"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.870000491549228 bestIt: 4 CE: -0.870000491549228 featOrth: 0.035867020333976"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.870000491549228 bestIt: 4 CE: -0.665096250118556 featOrth: 0.00614621932204562"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.870000491549228 bestIt: 4 CE: -0.76390214331349 featOrth: 0.00369478829577367"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.870000491549228 bestIt: 4 CE: -0.76390214331349 featOrth: 0.00369478829577367"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.870000491549228 bestIt: 4 CE: -0.724972796721192 featOrth: 0.00830243687373432"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
 <span><span class="co">#&gt; [1] "Stiefelx10x10"</span></span>
 <span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
 <span><span class="co">#&gt; [1] 0.99</span></span>
@@ -768,35 +1514,429 @@ <h3 id="evaluating-machine-learning-objective-functions">Evaluating Machine Lear
 <span><span class="co">#&gt; [1] "lineSearch"</span></span>
 <span><span class="co">#&gt; [1] "Stiefel" "10"      "10"     </span></span>
 <span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
-<span><span class="co">#&gt; [1] "initialDataTerm: -0.256180683310025  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.650640207873091 bestIt: 1 CE: -0.650640207873091"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.650640207873091 bestIt: 1 CE: -0.218388179246398"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.696319915034635 bestIt: 3 CE: -0.696319915034635"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.759893913629972 bestIt: 4 CE: -0.759893913629972"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.768262080301378 bestIt: 5 CE: -0.768262080301378"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.768262080301378 bestIt: 5 CE: -0.765977672674105"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.768262080301378 bestIt: 5 CE: -0.765336283833082"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.768262080301378 bestIt: 5 CE: -0.765336283833082"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.768262080301378 bestIt: 5 CE: -0.765336283833082"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.768262080301378 bestIt: 5 CE: -0.765336283833082"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.768262080301378 bestIt: 5 CE: -0.552849247389965"</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 1.25100508279622  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.237184452645269 bestIt: 1 CE: 0.237184452645269 featOrth: 2.30359272935859e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.177599700677383 bestIt: 2 CE: 0.177599700677383 featOrth: 0.0021810042697324"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.0999614015920791 bestIt: 3 CE: 0.0999614015920791 featOrth: 0.000518081150273759"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.0849516636360191 bestIt: 4 CE: 0.0849516636360191 featOrth: 0.000252183506036478"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.070249291003082 bestIt: 5 CE: 0.070249291003082 featOrth: 0.000331533423115467"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.0615332341061901 bestIt: 6 CE: 0.0615332341061901 featOrth: 0.000325894831012297"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0544254642804118 bestIt: 7 CE: 0.0544254642804118 featOrth: 0.000187380292101023"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0477093129745336 bestIt: 8 CE: 0.0477093129745336 featOrth: 0.000244995225826676"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0420136566709335 bestIt: 9 CE: 0.0420136566709335 featOrth: 0.000314346334619658"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0393065577033466 bestIt: 10 CE: 0.0393065577033466 featOrth: 0.00024407719736889"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.034948353669605 bestIt: 11 CE: 0.034948353669605 featOrth: 0.000319069930972649"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0324058289401098 bestIt: 12 CE: 0.0324058289401098 featOrth: 0.000231384104514991"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0315140407665402 bestIt: 13 CE: 0.0315140407665402 featOrth: 0.000219754876544245"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0308658941679237 bestIt: 14 CE: 0.0308658941679237 featOrth: 0.0002230773206307"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0305148687544833 bestIt: 15 CE: 0.0305148687544833 featOrth: 0.000220591516771638"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0301775906910979 bestIt: 16 CE: 0.0301775906910979 featOrth: 0.000221581310191778"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0299333373843949 bestIt: 17 CE: 0.0299333373843949 featOrth: 0.000218653199634132"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0297417813691914 bestIt: 18 CE: 0.0297417813691914 featOrth: 0.000215683478831739"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0284583581811108 bestIt: 19 CE: 0.0284583581811108 featOrth: 0.000262134082198118"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0283090715319203 bestIt: 20 CE: 0.0283090715319203 featOrth: 0.000263441810054545"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0281816241181519 bestIt: 21 CE: 0.0281816241181519 featOrth: 0.000263737008431142"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0281084007054559 bestIt: 22 CE: 0.0281084007054559 featOrth: 0.000261704317188562"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0280370451702563 bestIt: 23 CE: 0.0280370451702563 featOrth: 0.000262461410401017"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.02799516500076 bestIt: 24 CE: 0.02799516500076 featOrth: 0.000261848629714436"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0254802594741286 bestIt: 25 CE: 0.0254802594741286 featOrth: 0.000387260166832771"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.0254464901788025 bestIt: 26 CE: 0.0254464901788025 featOrth: 0.000386866039082069"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0253905273866932 bestIt: 27 CE: 0.0253905273866932 featOrth: 0.000387622273501941"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0253905273866932 bestIt: 27 CE: 0.0253905273866932 featOrth: 0.000387622273501941"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0253603858648398 bestIt: 29 CE: 0.0253603858648398 featOrth: 0.000387480160495074"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0253247498756749 bestIt: 30 CE: 0.0253247498756749 featOrth: 0.000388021992261607"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0245547929883146 bestIt: 31 CE: 0.0245547929883146 featOrth: 0.000387412290101146"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0245547929883146 bestIt: 31 CE: 0.0245547929883146 featOrth: 0.000387412290101146"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.0245353283893763 bestIt: 33 CE: 0.0245353283893763 featOrth: 0.000387293217881928"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.0245005577384855 bestIt: 34 CE: 0.0245005577384855 featOrth: 0.000387759853830104"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.0245005577384855 bestIt: 34 CE: 0.0245005577384855 featOrth: 0.000387759853830104"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.0202640901707436 bestIt: 36 CE: 0.0202640901707436 featOrth: 0.000555056743036319"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.0182499103673104 bestIt: 37 CE: 0.0182499103673104 featOrth: 0.000356251728970078"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.0143932271128292 bestIt: 38 CE: 0.0143932271128292 featOrth: 0.000398033659114448"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 39 bestEv: 0.0143932271128292 bestIt: 38 CE: 0.0143932271128292 featOrth: 0.000398033659114448"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 40 bestEv: 0.0143932271128292 bestIt: 38 CE: 0.0143932271128292 featOrth: 0.000398033659114448"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 41 bestEv: 0.0143932271128292 bestIt: 38 CE: 0.0143932271128292 featOrth: 0.000398033659114448"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 42 bestEv: 0.0143932271128292 bestIt: 38 CE: 0.0143932271128292 featOrth: 0.000398033659114448"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 43 bestEv: 0.0143932271128292 bestIt: 38 CE: 0.0143932271128292 featOrth: 0.000398033659114448"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 44 bestEv: 0.0143932271128292 bestIt: 38 CE: 0.0143932271128292 featOrth: 0.000398033659114448"</span></span>
 <span><span class="co">#&gt; [1] "improvement"</span></span>
 <span><span class="co">#&gt;   nsimlr objectiver mixer ebber    optimus    constraint final_energy</span></span>
-<span><span class="co">#&gt; 1      2        cca   pca  0.99 lineSearch Stiefelx10x10     15.98724</span></span>
+<span><span class="co">#&gt; 1      2 regression   ica  0.99 lineSearch Stiefelx10x10     21.58253</span></span>
 <span><span class="co">#&gt;   prescaling1    prescaling2 prescaling3 sparval1 sparval2 sparval3 positivity1</span></span>
 <span><span class="co">#&gt; 1      robust centerAndScale          np      0.5      0.5      0.5    positive</span></span>
 <span><span class="co">#&gt;   positivity2 positivity3 perm     m1_m2     m1_m3     m2_m3</span></span>
-<span><span class="co">#&gt; 1    positive    positive    0 0.7731677 0.4217462 0.4443339</span></span>
-<span><span class="co">#&gt;              PC1         PC2</span></span>
-<span><span class="co">#&gt; m3.1 0.000000000 0.001482357</span></span>
-<span><span class="co">#&gt; m3.2 0.003105033 0.000000000</span></span>
-<span><span class="co">#&gt; m3.3 0.000000000 0.010686503</span></span>
-<span><span class="co">#&gt; m3.4 0.000000000 0.000000000</span></span>
-<span><span class="co">#&gt; m3.5 0.000000000 0.023650730</span></span>
-<span><span class="co">#&gt; m3.6 0.016423998 0.013936366</span></span>
+<span><span class="co">#&gt; 1    positive    positive    0 0.6219873 0.6071353 0.6425949</span></span>
+<span><span class="co">#&gt;               PC1          PC2</span></span>
+<span><span class="co">#&gt; m3.1 0.0262858862 0.0020503009</span></span>
+<span><span class="co">#&gt; m3.2 0.0005042239 0.0000000000</span></span>
+<span><span class="co">#&gt; m3.3 0.0402618578 0.0000000000</span></span>
+<span><span class="co">#&gt; m3.4 0.0016642673 0.0000000000</span></span>
+<span><span class="co">#&gt; m3.5 0.0078357849 0.0003073337</span></span>
+<span><span class="co">#&gt; m3.6 0.0000000000 0.0207367474</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx10x10"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "10"      "10"     </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.256180683310025  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.589262575076857 bestIt: 1 CE: -0.589262575076857 featOrth: 0.0172419643760453"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.802681897865032 bestIt: 2 CE: -0.802681897865032 featOrth: 0.00547056235091384"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.802681897865032 bestIt: 2 CE: -0.45018130150942 featOrth: 0.00235515342063817"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.802681897865032 bestIt: 2 CE: -0.393866790928124 featOrth: 0.00365306779475794"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.802681897865032 bestIt: 2 CE: -0.177118967334056 featOrth: 0.00418150121024386"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.802681897865032 bestIt: 2 CE: -0.177118967334056 featOrth: 0.00418150121024386"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.802681897865032 bestIt: 2 CE: -0.618032405040395 featOrth: 0.000840863613391948"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.802681897865032 bestIt: 2 CE: -0.624359198046464 featOrth: 0.000735247028386376"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx10x10"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "10"      "10"     </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 1.25100508279622  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.237010555484801 bestIt: 1 CE: 0.237010555484801 featOrth: 2.30359272935859e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.172750061941759 bestIt: 2 CE: 0.172750061941759 featOrth: 0.00070192842066783"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.105721656331601 bestIt: 3 CE: 0.105721656331601 featOrth: 0.000871443566070205"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.0851681109040682 bestIt: 4 CE: 0.0851681109040682 featOrth: 0.000244523050871127"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.0725426721916632 bestIt: 5 CE: 0.0725426721916632 featOrth: 0.000568407447180727"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.0698280256718895 bestIt: 6 CE: 0.0698280256718895 featOrth: 0.000367800496903251"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0603288730019936 bestIt: 7 CE: 0.0603288730019936 featOrth: 0.000545129736778462"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0577217450104461 bestIt: 8 CE: 0.0577217450104461 featOrth: 0.000544243432961393"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0548997192135438 bestIt: 9 CE: 0.0548997192135438 featOrth: 0.000473344989696728"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0544302145796083 bestIt: 10 CE: 0.0544302145796083 featOrth: 0.000479602671629746"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.048917740475118 bestIt: 11 CE: 0.048917740475118 featOrth: 0.000704547287887674"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0451855720506414 bestIt: 12 CE: 0.0451855720506413 featOrth: 0.000664277288002216"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0447154307153375 bestIt: 13 CE: 0.0447154307153375 featOrth: 0.000649468412050496"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0444540413025522 bestIt: 14 CE: 0.0444540413025522 featOrth: 0.000658579394382493"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.044176887093219 bestIt: 15 CE: 0.044176887093219 featOrth: 0.000649506643691256"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0400423960304044 bestIt: 16 CE: 0.0400423960304044 featOrth: 0.00104048276273229"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0396402598982318 bestIt: 17 CE: 0.0396402598982318 featOrth: 0.000671497336361665"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0393978268455926 bestIt: 18 CE: 0.0393978268455926 featOrth: 0.000671943446595151"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0277002435931791 bestIt: 19 CE: 0.0277002435931791 featOrth: 0.00118547640755665"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0275479699819947 bestIt: 20 CE: 0.0275479699819947 featOrth: 0.000504914244033793"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0199475218259628 bestIt: 21 CE: 0.0199475218259628 featOrth: 0.00060089365413513"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0199475218259628 bestIt: 21 CE: 0.0236993683404917 featOrth: 0.000425507959992126"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0199475218259628 bestIt: 21 CE: 0.0246002861798785 featOrth: 0.000425806622525975"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0175243100082191 bestIt: 24 CE: 0.0175243100082191 featOrth: 0.00033967681267098"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0150764322410969 bestIt: 25 CE: 0.0150764322410969 featOrth: 0.000108225485089776"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.012816328157478 bestIt: 26 CE: 0.012816328157478 featOrth: 5.10255654806141e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0126440570492239 bestIt: 27 CE: 0.0126440570492239 featOrth: 6.02555131029619e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0108296538695813 bestIt: 28 CE: 0.0108296538695813 featOrth: 4.0908005110269e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0102965035931448 bestIt: 29 CE: 0.0102965035931448 featOrth: 3.73358725191403e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0102965035931448 bestIt: 29 CE: 0.0106740341315138 featOrth: 3.8942045607644e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0102965035931448 bestIt: 29 CE: 0.0107620103168178 featOrth: 3.86567326621483e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0102965035931448 bestIt: 29 CE: 0.010756907247634 featOrth: 3.92782991565723e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.0102965035931448 bestIt: 29 CE: 0.010756907247634 featOrth: 3.92782991565723e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.0102965035931448 bestIt: 29 CE: 0.010756907247634 featOrth: 3.92782991565723e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.0102965035931448 bestIt: 29 CE: 0.0107542223321491 featOrth: 3.87525676073583e-05"</span></span>
 <span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
 <span><span class="co">#&gt; [1] "cca"</span></span>
 <span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx10x10"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "10"      "10"     </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.256180683310025  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.676830154047982 bestIt: 1 CE: -0.676830154047982 featOrth: 0.0172419643760453"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.676830154047982 bestIt: 1 CE: -0.66639542659054 featOrth: 0.0156728395227006"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.676830154047982 bestIt: 1 CE: -0.66639542659054 featOrth: 0.0156728395227006"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.676830154047982 bestIt: 1 CE: -0.623344634483921 featOrth: 0.00694172432567053"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.861049755260674 bestIt: 5 CE: -0.861049755260674 featOrth: 0.0069305825452416"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.898951952157264 bestIt: 6 CE: -0.898951952157264 featOrth: 0.00474658475410599"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.907963675013332 bestIt: 7 CE: -0.907963675013332 featOrth: 0.00334674114785911"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.913123902103393 bestIt: 8 CE: -0.913123902103393 featOrth: 0.00349702308328047"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.915159842902505 bestIt: 9 CE: -0.915159842902505 featOrth: 0.00336215974924143"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.915159842902505 bestIt: 9 CE: -0.915152393403575 featOrth: 0.00323214702659185"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.915159842902505 bestIt: 9 CE: -0.914274821230272 featOrth: 0.00320671240713788"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.915159842902505 bestIt: 9 CE: -0.912934026245232 featOrth: 0.00320700537410178"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.915159842902505 bestIt: 9 CE: -0.91189578515646 featOrth: 0.00312533724802569"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.915159842902505 bestIt: 9 CE: -0.91189578515646 featOrth: 0.00312533724802569"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.915159842902505 bestIt: 9 CE: -0.91189578515646 featOrth: 0.00312533724802569"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "100"     "1"      </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.244409518024852 bestIt: 1 CE: 0.244409518024852 featOrth: 3.89547838455626e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.185410613659155 bestIt: 2 CE: 0.185410613659155 featOrth: 3.04788793311056e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.149635009305485 bestIt: 3 CE: 0.149635009305485 featOrth: 8.50034711644909e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.129617920099729 bestIt: 4 CE: 0.129617920099729 featOrth: 9.42363837686497e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.113601398787313 bestIt: 5 CE: 0.113601398787313 featOrth: 0.000110715053865568"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.107582609882827 bestIt: 6 CE: 0.107582609882827 featOrth: 7.42682048346664e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0975727391223358 bestIt: 7 CE: 0.0975727391223358 featOrth: 0.000149482507878604"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.092900491218454 bestIt: 8 CE: 0.092900491218454 featOrth: 0.000106012582900065"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.089133970058259 bestIt: 9 CE: 0.089133970058259 featOrth: 0.000132971534329456"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0804887030630765 bestIt: 10 CE: 0.0804887030630765 featOrth: 0.000154414066084388"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0744011510014059 bestIt: 11 CE: 0.0744011510014059 featOrth: 9.15665451250348e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0705973287082171 bestIt: 12 CE: 0.0705973287082171 featOrth: 0.000106382804705848"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0680433855858336 bestIt: 13 CE: 0.0680433855858336 featOrth: 0.000106305429433417"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0660838473801095 bestIt: 14 CE: 0.0660838473801095 featOrth: 0.000105780233005938"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "100"     "1"      </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.178173269808786 bestIt: 1 CE: 0.178173269808786 featOrth: 0.0130418824664029"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.423194242117571 bestIt: 2 CE: -0.423194242117571 featOrth: 0.000900159789533884"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.532959971137901 bestIt: 3 CE: -0.532959971137901 featOrth: 0.000474478738428326"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.538651341927223 bestIt: 4 CE: -0.538651341927223 featOrth: 0.000425030518142912"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.585251647128846 bestIt: 5 CE: -0.585251647128846 featOrth: 0.000651694254713825"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.597114592417786 bestIt: 6 CE: -0.597114592417786 featOrth: 0.000257980303133645"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.623233711320179 bestIt: 7 CE: -0.623233711320179 featOrth: 0.000242222593044334"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.623233711320179 bestIt: 7 CE: -0.619278317683527 featOrth: 0.000287340164564807"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.623233711320179 bestIt: 7 CE: -0.619278317683527 featOrth: 0.000287340164564807"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.623233711320179 bestIt: 7 CE: -0.610526759335308 featOrth: 0.000245353493933273"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.623233711320179 bestIt: 7 CE: -0.610526759335308 featOrth: 0.000245353493933273"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.623233711320179 bestIt: 7 CE: -0.610526759335308 featOrth: 0.000245353493933273"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.623233711320179 bestIt: 7 CE: -0.610526759335308 featOrth: 0.000245353493933273"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "100"     "1"      </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.244864666623697 bestIt: 1 CE: 0.244864666623697 featOrth: 3.89547838455626e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.182726912880005 bestIt: 2 CE: 0.182726912880005 featOrth: 4.29355373666028e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.145569313741478 bestIt: 3 CE: 0.145569313741478 featOrth: 9.44871052761846e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.126368268363636 bestIt: 4 CE: 0.126368268363636 featOrth: 6.6701743677141e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.108768525201795 bestIt: 5 CE: 0.108768525201795 featOrth: 0.00011072354814898"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.099792846033958 bestIt: 6 CE: 0.099792846033958 featOrth: 5.88136843499618e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0860403413066845 bestIt: 7 CE: 0.0860403413066845 featOrth: 0.000126174051205592"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0830437502840702 bestIt: 8 CE: 0.0830437502840702 featOrth: 0.00010385277642997"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0819594163350836 bestIt: 9 CE: 0.0819594163350836 featOrth: 0.000106084776627439"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0803262072503349 bestIt: 10 CE: 0.0803262072503349 featOrth: 0.000100774201568677"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0803262072503349 bestIt: 10 CE: 0.0803262072503349 featOrth: 0.000100774201568677"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0803262072503349 bestIt: 10 CE: 0.0803262072503349 featOrth: 0.000100774201568677"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0761161453537858 bestIt: 13 CE: 0.0761161453537858 featOrth: 0.000100221598213217"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.074232906203372 bestIt: 14 CE: 0.074232906203372 featOrth: 0.000103690332212682"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.074232906203372 bestIt: 14 CE: 0.074232906203372 featOrth: 0.000103690332212682"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0679942255302906 bestIt: 16 CE: 0.0679942255302906 featOrth: 0.000103317025325873"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.055562922629912 bestIt: 17 CE: 0.055562922629912 featOrth: 8.59257519184896e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0540278574272764 bestIt: 18 CE: 0.0540278574272764 featOrth: 9.0136433011892e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0540278574272764 bestIt: 18 CE: 0.0540278574272764 featOrth: 9.0136433011892e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.053053799053449 bestIt: 20 CE: 0.053053799053449 featOrth: 8.93229743661115e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0483273205272969 bestIt: 21 CE: 0.0483273205272969 featOrth: 9.7899265234853e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0483273205272969 bestIt: 21 CE: 0.0483273205272969 featOrth: 9.7899265234853e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0467067323804058 bestIt: 23 CE: 0.0467067323804058 featOrth: 0.000111970981430283"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0450276661300847 bestIt: 24 CE: 0.0450276661300847 featOrth: 9.8185823883934e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0441068152241325 bestIt: 25 CE: 0.0441068152241325 featOrth: 0.000101974141509545"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.043967455246281 bestIt: 26 CE: 0.043967455246281 featOrth: 9.7974192228666e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0436306752021084 bestIt: 27 CE: 0.0436306752021084 featOrth: 9.83037460825187e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0436215354018599 bestIt: 28 CE: 0.0436215354018599 featOrth: 9.83061926544647e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0435954521265963 bestIt: 29 CE: 0.0435954521265963 featOrth: 9.9461635212597e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0431223210441809 bestIt: 30 CE: 0.0431223210441809 featOrth: 9.6005526666986e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0431223210441809 bestIt: 30 CE: 0.0431282937822868 featOrth: 9.61653190022807e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0431098161280742 bestIt: 32 CE: 0.0431098161280742 featOrth: 9.63327920419066e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.0326794659814507 bestIt: 33 CE: 0.0326794659814507 featOrth: 0.000108127324111515"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.0322125396857474 bestIt: 34 CE: 0.0322125396857474 featOrth: 5.66838435285153e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.0257643671651978 bestIt: 35 CE: 0.0257643671651978 featOrth: 5.24758437395e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.0257643671651978 bestIt: 35 CE: 0.0257643671651978 featOrth: 5.24758437395e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 39 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 40 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 41 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 42 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 43 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "100"     "1"      </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.0784927377092236 bestIt: 1 CE: 0.0784927377092236 featOrth: 0.0130418824664029"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.388741166793332 bestIt: 2 CE: -0.388741166793332 featOrth: 0.00470371775161333"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.5163889909006 bestIt: 3 CE: -0.5163889909006 featOrth: 0.00104728874099313"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.627754835405277 bestIt: 4 CE: -0.627754835405277 featOrth: 0.00110350247125656"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.64039091950709 bestIt: 5 CE: -0.64039091950709 featOrth: 0.00111867915422283"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.64039091950709 bestIt: 5 CE: -0.64039091950709 featOrth: 0.00111867915422283"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.64039091950709 bestIt: 5 CE: -0.64039091950709 featOrth: 0.00111867915422283"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "100"     "1"      </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.244409518024852 bestIt: 1 CE: 0.244409518024852 featOrth: 3.89547838455626e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.185410613659155 bestIt: 2 CE: 0.185410613659155 featOrth: 3.04788793311056e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.149635009305485 bestIt: 3 CE: 0.149635009305485 featOrth: 8.50034711644909e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.129617920099729 bestIt: 4 CE: 0.129617920099729 featOrth: 9.42363837686497e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.113601398787313 bestIt: 5 CE: 0.113601398787313 featOrth: 0.000110715053865568"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.107582609882827 bestIt: 6 CE: 0.107582609882827 featOrth: 7.42682048346664e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0975727391223358 bestIt: 7 CE: 0.0975727391223358 featOrth: 0.000149482507878604"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.092900491218454 bestIt: 8 CE: 0.092900491218454 featOrth: 0.000106012582900065"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.089133970058259 bestIt: 9 CE: 0.089133970058259 featOrth: 0.000132971534329456"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0804887030630765 bestIt: 10 CE: 0.0804887030630765 featOrth: 0.000154414066084388"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0744011510014059 bestIt: 11 CE: 0.0744011510014059 featOrth: 9.15665451250348e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0705973287082171 bestIt: 12 CE: 0.0705973287082171 featOrth: 0.000106382804705848"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0680433855858336 bestIt: 13 CE: 0.0680433855858336 featOrth: 0.000106305429433417"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0660838473801095 bestIt: 14 CE: 0.0660838473801095 featOrth: 0.000105780233005938"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0622525495206674 bestIt: 15 CE: 0.0622525495206674 featOrth: 0.000107143813253038"</span></span>
+<span><span class="co">#&gt; i 30 ...[1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "100"     "1"      </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.178173269808786 bestIt: 1 CE: 0.178173269808786 featOrth: 0.0130418824664029"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.423194242117571 bestIt: 2 CE: -0.423194242117571 featOrth: 0.000900159789533884"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.532959971137901 bestIt: 3 CE: -0.532959971137901 featOrth: 0.000474478738428326"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.538651341927223 bestIt: 4 CE: -0.538651341927223 featOrth: 0.000425030518142912"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.585251647128846 bestIt: 5 CE: -0.585251647128846 featOrth: 0.000651694254713825"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.597114592417786 bestIt: 6 CE: -0.597114592417786 featOrth: 0.000257980303133645"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.623233711320179 bestIt: 7 CE: -0.623233711320179 featOrth: 0.000242222593044334"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.623233711320179 bestIt: 7 CE: -0.619278317683527 featOrth: 0.000287340164564807"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.623233711320179 bestIt: 7 CE: -0.619278317683527 featOrth: 0.000287340164564807"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.623233711320179 bestIt: 7 CE: -0.610526759335308 featOrth: 0.000245353493933273"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.623233711320179 bestIt: 7 CE: -0.610526759335308 featOrth: 0.000245353493933273"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.623233711320179 bestIt: 7 CE: -0.610526759335308 featOrth: 0.000245353493933273"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.623233711320179 bestIt: 7 CE: -0.610526759335308 featOrth: 0.000245353493933273"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "100"     "1"      </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.244864666623697 bestIt: 1 CE: 0.244864666623697 featOrth: 3.89547838455626e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.182726912880005 bestIt: 2 CE: 0.182726912880005 featOrth: 4.29355373666028e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.145569313741478 bestIt: 3 CE: 0.145569313741478 featOrth: 9.44871052761846e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.126368268363636 bestIt: 4 CE: 0.126368268363636 featOrth: 6.6701743677141e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.108768525201795 bestIt: 5 CE: 0.108768525201795 featOrth: 0.00011072354814898"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.099792846033958 bestIt: 6 CE: 0.099792846033958 featOrth: 5.88136843499618e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0860403413066845 bestIt: 7 CE: 0.0860403413066845 featOrth: 0.000126174051205592"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0830437502840702 bestIt: 8 CE: 0.0830437502840702 featOrth: 0.00010385277642997"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0819594163350836 bestIt: 9 CE: 0.0819594163350836 featOrth: 0.000106084776627439"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0803262072503349 bestIt: 10 CE: 0.0803262072503349 featOrth: 0.000100774201568677"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0803262072503349 bestIt: 10 CE: 0.0803262072503349 featOrth: 0.000100774201568677"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0803262072503349 bestIt: 10 CE: 0.0803262072503349 featOrth: 0.000100774201568677"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0761161453537858 bestIt: 13 CE: 0.0761161453537858 featOrth: 0.000100221598213217"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.074232906203372 bestIt: 14 CE: 0.074232906203372 featOrth: 0.000103690332212682"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.074232906203372 bestIt: 14 CE: 0.074232906203372 featOrth: 0.000103690332212682"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0679942255302906 bestIt: 16 CE: 0.0679942255302906 featOrth: 0.000103317025325873"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.055562922629912 bestIt: 17 CE: 0.055562922629912 featOrth: 8.59257519184896e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0540278574272764 bestIt: 18 CE: 0.0540278574272764 featOrth: 9.0136433011892e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0540278574272764 bestIt: 18 CE: 0.0540278574272764 featOrth: 9.0136433011892e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.053053799053449 bestIt: 20 CE: 0.053053799053449 featOrth: 8.93229743661115e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0483273205272969 bestIt: 21 CE: 0.0483273205272969 featOrth: 9.7899265234853e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0483273205272969 bestIt: 21 CE: 0.0483273205272969 featOrth: 9.7899265234853e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0467067323804058 bestIt: 23 CE: 0.0467067323804058 featOrth: 0.000111970981430283"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0450276661300847 bestIt: 24 CE: 0.0450276661300847 featOrth: 9.8185823883934e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0441068152241325 bestIt: 25 CE: 0.0441068152241325 featOrth: 0.000101974141509545"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.043967455246281 bestIt: 26 CE: 0.043967455246281 featOrth: 9.7974192228666e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0436306752021084 bestIt: 27 CE: 0.0436306752021084 featOrth: 9.83037460825187e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0436215354018599 bestIt: 28 CE: 0.0436215354018599 featOrth: 9.83061926544647e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0435954521265963 bestIt: 29 CE: 0.0435954521265963 featOrth: 9.9461635212597e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0431223210441809 bestIt: 30 CE: 0.0431223210441809 featOrth: 9.6005526666986e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0431223210441809 bestIt: 30 CE: 0.0431282937822868 featOrth: 9.61653190022807e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0431098161280742 bestIt: 32 CE: 0.0431098161280742 featOrth: 9.63327920419066e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.0326794659814507 bestIt: 33 CE: 0.0326794659814507 featOrth: 0.000108127324111515"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.0322125396857474 bestIt: 34 CE: 0.0322125396857474 featOrth: 5.66838435285153e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.0257643671651978 bestIt: 35 CE: 0.0257643671651978 featOrth: 5.24758437395e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.0257643671651978 bestIt: 35 CE: 0.0257643671651978 featOrth: 5.24758437395e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 39 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 40 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 41 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 42 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 43 bestEv: 0.0242625458379577 bestIt: 37 CE: 0.0242625458379577 featOrth: 6.42392859057203e-05"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "100"     "1"      </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.0784927377092236 bestIt: 1 CE: 0.0784927377092236 featOrth: 0.0130418824664029"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.388741166793332 bestIt: 2 CE: -0.388741166793332 featOrth: 0.00470371775161333"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.5163889909006 bestIt: 3 CE: -0.5163889909006 featOrth: 0.00104728874099313"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.627754835405277 bestIt: 4 CE: -0.627754835405277 featOrth: 0.00110350247125656"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.64039091950709 bestIt: 5 CE: -0.64039091950709 featOrth: 0.00111867915422283"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.64039091950709 bestIt: 5 CE: -0.64039091950709 featOrth: 0.00111867915422283"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.64039091950709 bestIt: 5 CE: -0.64039091950709 featOrth: 0.00111867915422283"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.657513981766222 bestIt: 8 CE: -0.657513981766222 featOrth: 0.000691235453335433"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
 <span><span class="co">#&gt; [1] "Stiefelx1x1"</span></span>
 <span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
 <span><span class="co">#&gt; [1] 0.99</span></span>
@@ -804,55 +1944,176 @@ <h3 id="evaluating-machine-learning-objective-functions">Evaluating Machine Lear
 <span><span class="co">#&gt; [1] "lineSearch"</span></span>
 <span><span class="co">#&gt; [1] "Stiefel" "1"       "1"      </span></span>
 <span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
-<span><span class="co">#&gt; [1] "initialDataTerm: -0.857027012460654  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.47653047609036 bestIt: 1 CE: -0.47653047609036"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.694771385142719 bestIt: 2 CE: -0.694771385142719"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.837662061497179 bestIt: 3 CE: -0.83766206149718"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.845114841797893 bestIt: 4 CE: -0.845114841797893"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.87451301199215 bestIt: 5 CE: -0.87451301199215"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.87451301199215 bestIt: 5 CE: -0.874234379955215"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.875228992424385 bestIt: 7 CE: -0.875228992424385"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.884763242068898 bestIt: 8 CE: -0.884763242068898"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.894700997850001 bestIt: 9 CE: -0.894700997850001"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.894700997850001 bestIt: 9 CE: -0.881229074835642"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.89960923703501 bestIt: 11 CE: -0.89960923703501"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.908692262274978 bestIt: 12 CE: -0.908692262274978"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.908692262274978 bestIt: 12 CE: -0.902799735588814"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.908692262274978 bestIt: 12 CE: -0.902799735588814"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.908692262274978 bestIt: 12 CE: -0.87759749925849"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: -0.908692262274978 bestIt: 12 CE: -0.87759749925849"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: -0.908692262274978 bestIt: 12 CE: -0.87759749925849"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: -0.908692262274978 bestIt: 12 CE: -0.87759749925849"</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 0.650158753645586  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.236569233895379 bestIt: 1 CE: 0.236569233895379 featOrth: 0.00512043911850549"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.112606077529469 bestIt: 2 CE: 0.112606077529469 featOrth: 0.0082816808527204"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.0617065663153942 bestIt: 3 CE: 0.0617065663153942 featOrth: 0.00483270576797053"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.0472628795826866 bestIt: 4 CE: 0.0472628795826866 featOrth: 0.00140429651401662"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.0378332435737168 bestIt: 5 CE: 0.0378332435737168 featOrth: 0.00113772356986332"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.0308520102354881 bestIt: 6 CE: 0.0308520102354881 featOrth: 0.00238826504478486"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0278038731191662 bestIt: 7 CE: 0.0278038731191662 featOrth: 0.000886928275617233"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0230590094974394 bestIt: 8 CE: 0.0230590094974394 featOrth: 0.00100103915285884"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0212358136705291 bestIt: 9 CE: 0.0212358136705291 featOrth: 0.000847817640488128"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0187360970616038 bestIt: 10 CE: 0.0187360970616038 featOrth: 0.000659460270594862"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0170045660125367 bestIt: 11 CE: 0.0170045660125367 featOrth: 0.000971712259863401"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0160315120317362 bestIt: 12 CE: 0.0160315120317362 featOrth: 0.00057812505008492"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0156997182538691 bestIt: 13 CE: 0.0156997182538691 featOrth: 0.000838727553198581"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0150670500134963 bestIt: 14 CE: 0.0150670500134963 featOrth: 0.000592116097355846"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.014594767901857 bestIt: 15 CE: 0.014594767901857 featOrth: 0.00072247197174257"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0137730513585243 bestIt: 16 CE: 0.0137730513585243 featOrth: 0.00056515649790679"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0126870741435571 bestIt: 17 CE: 0.0126870741435571 featOrth: 0.00123175482946092"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0118237598155368 bestIt: 18 CE: 0.0118237598155368 featOrth: 0.000132938017310278"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.01115507095145 bestIt: 19 CE: 0.01115507095145 featOrth: 0.000240049725997153"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.010881542799504 bestIt: 20 CE: 0.010881542799504 featOrth: 8.33387312691956e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.010389783611156 bestIt: 21 CE: 0.010389783611156 featOrth: 0.000241416638011043"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0101441446732025 bestIt: 22 CE: 0.0101441446732025 featOrth: 3.99100279961919e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.00994480470832473 bestIt: 23 CE: 0.00994480470832473 featOrth: 0.000101220089048375"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.009760034409719 bestIt: 24 CE: 0.009760034409719 featOrth: 2.33539550496122e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.00963992796588749 bestIt: 25 CE: 0.00963992796588749 featOrth: 4.23218468943684e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.00953478940981701 bestIt: 26 CE: 0.00953478940981701 featOrth: 1.46842597795038e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.00944371430516993 bestIt: 27 CE: 0.00944371430516993 featOrth: 3.06677155043263e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.00944371430516993 bestIt: 27 CE: 0.00955120372009428 featOrth: 1.44859422279995e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.00919549132205526 bestIt: 29 CE: 0.00919549132205526 featOrth: 1.31634104334638e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.00919549132205526 bestIt: 29 CE: 0.00940677775295125 featOrth: 1.00773324814957e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.00904510200260016 bestIt: 31 CE: 0.00904510200260016 featOrth: 4.9160213740596e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.00904510200260016 bestIt: 31 CE: 0.00930025551872731 featOrth: 7.51552637060555e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.00896966508826725 bestIt: 33 CE: 0.00896966508826725 featOrth: 4.14737422353571e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.00896966508826725 bestIt: 33 CE: 0.0091814521691468 featOrth: 5.67256870098652e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.00896966508826725 bestIt: 33 CE: 0.00916924378197662 featOrth: 8.91866896678233e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.00884435147899012 bestIt: 36 CE: 0.00884435147899012 featOrth: 2.94657666547126e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.00882639147984077 bestIt: 37 CE: 0.00882639147984077 featOrth: 3.68638830234849e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.00877456084769578 bestIt: 38 CE: 0.00877456084769578 featOrth: 4.08948943715028e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 39 bestEv: 0.0087721748264898 bestIt: 39 CE: 0.0087721748264898 featOrth: 2.91419804802446e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 40 bestEv: 0.00871448601324232 bestIt: 40 CE: 0.00871448601324231 featOrth: 2.89484708066768e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 41 bestEv: 0.00871448601324232 bestIt: 40 CE: 0.00871448601324231 featOrth: 2.89484708066768e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 42 bestEv: 0.00871448601324232 bestIt: 40 CE: 0.00871448601324231 featOrth: 2.89484708066768e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 43 bestEv: 0.00871448601324232 bestIt: 40 CE: 0.00871448601324231 featOrth: 2.89484708066768e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 44 bestEv: 0.00871448601324232 bestIt: 40 CE: 0.00871448601324231 featOrth: 2.89484708066768e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 45 bestEv: 0.00871448601324232 bestIt: 40 CE: 0.00871448601324231 featOrth: 2.89484708066768e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 46 bestEv: 0.00863149307035498 bestIt: 46 CE: 0.00863149307035498 featOrth: 3.74440617879053e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 47 bestEv: 0.00863149307035498 bestIt: 46 CE: 0.00863598065158414 featOrth: 3.77723821356628e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 48 bestEv: 0.00860232648206244 bestIt: 48 CE: 0.00860232648206244 featOrth: 2.66138796923611e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 49 bestEv: 0.00860232648206244 bestIt: 48 CE: 0.00862219794273197 featOrth: 3.06202077120264e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 50 bestEv: 0.00858413111448027 bestIt: 50 CE: 0.00858413111448027 featOrth: 2.43189050299662e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 51 bestEv: 0.00858413111448027 bestIt: 50 CE: 0.0086099566730178 featOrth: 2.65882372308856e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 52 bestEv: 0.00858413111448027 bestIt: 50 CE: 0.0086099566730178 featOrth: 2.65882372308856e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 53 bestEv: 0.00856987038143179 bestIt: 53 CE: 0.00856987038143179 featOrth: 2.32450390668158e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 54 bestEv: 0.00856987038143179 bestIt: 53 CE: 0.00856987038143179 featOrth: 2.32450390668158e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 55 bestEv: 0.00856987038143179 bestIt: 53 CE: 0.00856987038143179 featOrth: 2.32450390668158e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 56 bestEv: 0.00856987038143179 bestIt: 53 CE: 0.00856987038143179 featOrth: 2.32450390668158e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 57 bestEv: 0.00856987038143179 bestIt: 53 CE: 0.00856987038143179 featOrth: 2.32450390668158e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 58 bestEv: 0.00856987038143179 bestIt: 53 CE: 0.00860420395930806 featOrth: 2.46291810489728e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 59 bestEv: 0.00856033029009228 bestIt: 59 CE: 0.00856033029009228 featOrth: 2.24772172603627e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 60 bestEv: 0.00856033029009228 bestIt: 59 CE: 0.00856033029009228 featOrth: 2.24772172603627e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 61 bestEv: 0.00856033029009228 bestIt: 59 CE: 0.00856033029009228 featOrth: 2.24772172603627e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 62 bestEv: 0.00856033029009228 bestIt: 59 CE: 0.00856033029009228 featOrth: 2.24772172603627e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 63 bestEv: 0.00856033029009228 bestIt: 59 CE: 0.00856033029009228 featOrth: 2.24772172603627e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 64 bestEv: 0.00856033029009228 bestIt: 59 CE: 0.00859243327614568 featOrth: 2.31117597118453e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 65 bestEv: 0.00856033029009228 bestIt: 59 CE: 0.00859243327614568 featOrth: 2.31117597118453e-06"</span></span>
 <span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
 <span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx1x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "1"       "1"      </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.857027012460654  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.639499395785757 bestIt: 1 CE: -0.639499395785757 featOrth: 0.0372846638855747"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.639499395785757 bestIt: 1 CE: -0.615468955092181 featOrth: 0.0349563378555909"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.644823165838176 bestIt: 3 CE: -0.644823165838176 featOrth: 0.0297440345082408"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.645945893759142 bestIt: 4 CE: -0.645945893759142 featOrth: 0.0230013772800576"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.645945893759142 bestIt: 4 CE: -0.645074503571979 featOrth: 0.0227467039019114"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.645945893759142 bestIt: 4 CE: -0.644494361594977 featOrth: 0.0228703204309815"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.665644929588053 bestIt: 7 CE: -0.665644929588053 featOrth: 0.0261824049548822"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.665644929588053 bestIt: 7 CE: -0.61534001237917 featOrth: 0.0131429313965438"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.665644929588053 bestIt: 7 CE: -0.617428698532817 featOrth: 0.00914875182561813"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.665644929588053 bestIt: 7 CE: -0.40019903987781 featOrth: 0.0166560299307265"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.665644929588053 bestIt: 7 CE: -0.399266317506881 featOrth: 0.0212318240536157"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.665644929588053 bestIt: 7 CE: -0.623065997760647 featOrth: 0.0228100470424045"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.665644929588053 bestIt: 7 CE: -0.625721284795678 featOrth: 0.0215522874160391"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
 <span><span class="co">#&gt; [1] "pca"</span></span>
-<span><span class="co">#&gt; [1] "Stiefelx0.1x0.1"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx1x1"</span></span>
 <span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
 <span><span class="co">#&gt; [1] 0.99</span></span>
 <span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
 <span><span class="co">#&gt; [1] "lineSearch"</span></span>
-<span><span class="co">#&gt; [1] "Stiefel" "0.1"     "0.1"    </span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "1"       "1"      </span></span>
 <span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
-<span><span class="co">#&gt; [1] "initialDataTerm: -0.917111645375717  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.355967404820103 bestIt: 1 CE: -0.355967404820103"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.355967404820103 bestIt: 1 CE: -0.302103177973874"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.671490785475746 bestIt: 3 CE: -0.671490785475746"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.858188887620578 bestIt: 4 CE: -0.858188887620578"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.874754096348496 bestIt: 5 CE: -0.874754096348496"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.874754096348496 bestIt: 5 CE: -0.850267139384837"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.874754096348496 bestIt: 5 CE: -0.761710261441642"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.87961111056513 bestIt: 8 CE: -0.87961111056513"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.87961111056513 bestIt: 8 CE: -0.856383172165312"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.905545909098392 bestIt: 10 CE: -0.905545909098392"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.905545909098392 bestIt: 10 CE: -0.886125641764854"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.905545909098392 bestIt: 10 CE: -0.883007804056776"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.905545909098392 bestIt: 10 CE: -0.882883225209442"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.905545909098392 bestIt: 10 CE: -0.903855294741201"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.905545909098392 bestIt: 10 CE: -0.874918255105305"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: -0.905545909098392 bestIt: 10 CE: -0.871591364713644"</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 0.650158753645586  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.233297749819811 bestIt: 1 CE: 0.233297749819811 featOrth: 0.00512043911850549"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.111470831034556 bestIt: 2 CE: 0.111470831034556 featOrth: 0.0157376630691725"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.0705358473951956 bestIt: 3 CE: 0.0705358473951956 featOrth: 0.00174379997925788"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.0497710783367968 bestIt: 4 CE: 0.0497710783367968 featOrth: 0.00254257285965667"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.0429572396234593 bestIt: 5 CE: 0.0429572396234593 featOrth: 0.00241471379821711"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.033514893438499 bestIt: 6 CE: 0.033514893438499 featOrth: 0.00304229890423851"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0282911601998426 bestIt: 7 CE: 0.0282911601998426 featOrth: 0.00124486839515221"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0234105284838245 bestIt: 8 CE: 0.0234105284838245 featOrth: 0.00190610644981154"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0222081917690332 bestIt: 9 CE: 0.0222081917690332 featOrth: 0.00118895438697766"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0205083768813281 bestIt: 10 CE: 0.0205083768813281 featOrth: 0.00191309976821708"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0189021040102388 bestIt: 11 CE: 0.0189021040102388 featOrth: 0.000520031800722396"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0160772930900778 bestIt: 12 CE: 0.0160772930900778 featOrth: 0.00162999292983221"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0154854594354566 bestIt: 13 CE: 0.0154854594354566 featOrth: 0.00106171278006232"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.014839992441555 bestIt: 14 CE: 0.014839992441555 featOrth: 0.000389502076995408"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0132933488410567 bestIt: 15 CE: 0.0132933488410567 featOrth: 0.00118399333967163"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.012251917359122 bestIt: 16 CE: 0.012251917359122 featOrth: 0.000399727107124289"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0106298511382476 bestIt: 17 CE: 0.0106298511382476 featOrth: 0.000140738758069178"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0102663749158378 bestIt: 18 CE: 0.0102663749158378 featOrth: 1.85513243196915e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.010189472197943 bestIt: 19 CE: 0.010189472197943 featOrth: 1.74366119112469e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.00997658853035393 bestIt: 20 CE: 0.00997658853035393 featOrth: 4.3823374063171e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.00985855471576763 bestIt: 21 CE: 0.00985855471576763 featOrth: 3.57767327069528e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.00980265682632052 bestIt: 22 CE: 0.00980265682632052 featOrth: 3.88961451204264e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0096694223600456 bestIt: 23 CE: 0.0096694223600456 featOrth: 3.44265746382942e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.00963059133565779 bestIt: 24 CE: 0.00963059133565779 featOrth: 3.33574485512308e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.00957307032527707 bestIt: 25 CE: 0.00957307032527707 featOrth: 3.08617372602088e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.00955873756383294 bestIt: 26 CE: 0.00955873756383294 featOrth: 3.95382744516745e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.00952764576443303 bestIt: 27 CE: 0.00952764576443303 featOrth: 3.31895750799653e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.00951025311174746 bestIt: 28 CE: 0.00951025311174746 featOrth: 3.36046639233299e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.00951025311174746 bestIt: 28 CE: 0.00958380872011817 featOrth: 3.27915701063751e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.00951025311174746 bestIt: 28 CE: 0.00976615628331076 featOrth: 3.27496095282182e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.00950017639068665 bestIt: 31 CE: 0.00950017639068665 featOrth: 3.26179056234393e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.00950017639068665 bestIt: 31 CE: 0.00958884781315996 featOrth: 3.97974439464857e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.00936352185911501 bestIt: 33 CE: 0.00936352185911501 featOrth: 3.99790303014996e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.00936352185911501 bestIt: 33 CE: 0.00951048878912087 featOrth: 3.95697285268567e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.00936352185911501 bestIt: 33 CE: 0.00951048878912087 featOrth: 3.95697285268567e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.00936352185911501 bestIt: 33 CE: 0.00951048878912087 featOrth: 3.95697285268567e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.00936352185911501 bestIt: 33 CE: 0.00951048878912087 featOrth: 3.95697285268567e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.00936352185911501 bestIt: 33 CE: 0.00951048878912087 featOrth: 3.95697285268567e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 39 bestEv: 0.00932090318759156 bestIt: 39 CE: 0.00932090318759156 featOrth: 3.97233948781146e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 40 bestEv: 0.00932090318759156 bestIt: 39 CE: 0.00932090318759156 featOrth: 3.97233948781146e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 41 bestEv: 0.00932090318759156 bestIt: 39 CE: 0.00932090318759156 featOrth: 3.97233948781146e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 42 bestEv: 0.00932090318759156 bestIt: 39 CE: 0.00932090318759156 featOrth: 3.97233948781146e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 43 bestEv: 0.00932090318759156 bestIt: 39 CE: 0.00932090318759156 featOrth: 3.97233948781146e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 44 bestEv: 0.00932090318759156 bestIt: 39 CE: 0.00932090318759156 featOrth: 3.97233948781146e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 45 bestEv: 0.00932090318759156 bestIt: 39 CE: 0.00932090318759156 featOrth: 3.97233948781146e-05"</span></span>
 <span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
 <span><span class="co">#&gt; [1] "cca"</span></span>
 <span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "Stiefelx1x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "Stiefel" "1"       "1"      </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.857027012460654  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.647120427113086 bestIt: 1 CE: -0.647120427113086 featOrth: 0.0372846638855747"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.658711197552408 bestIt: 2 CE: -0.658711197552408 featOrth: 0.0382348242528437"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.883971767977673 bestIt: 3 CE: -0.883971767977673 featOrth: 0.0307552640783588"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.915675010641715 bestIt: 4 CE: -0.915675010641715 featOrth: 0.0366780895165292"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.915675010641715 bestIt: 4 CE: -0.893389339579292 featOrth: 0.00757009757242349"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.915675010641715 bestIt: 4 CE: -0.821217732023415 featOrth: 0.00880026787807739"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.915675010641715 bestIt: 4 CE: -0.698076301031294 featOrth: 0.0108666353940907"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.915675010641715 bestIt: 4 CE: -0.757166351017079 featOrth: 0.0117121846706184"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.915675010641715 bestIt: 4 CE: -0.877980765357414 featOrth: 0.0139731443240239"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.915675010641715 bestIt: 4 CE: -0.881792580952754 featOrth: 0.0222145588596332"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
 <span><span class="co">#&gt; [1] "orthox10x10"</span></span>
 <span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
 <span><span class="co">#&gt; [1] 0.99</span></span>
@@ -860,33 +2121,431 @@ <h3 id="evaluating-machine-learning-objective-functions">Evaluating Machine Lear
 <span><span class="co">#&gt; [1] "lineSearch"</span></span>
 <span><span class="co">#&gt; [1] "ortho" "10"    "10"   </span></span>
 <span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
-<span><span class="co">#&gt; [1] "initialDataTerm: -0.256180683310025  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.507312461403781 bestIt: 1 CE: -0.507312461403781"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.688154502294652 bestIt: 2 CE: -0.688154502294652"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.699671381310042 bestIt: 3 CE: -0.699671381310042"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.699671381310042 bestIt: 3 CE: -0.699671381310042"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.699671381310042 bestIt: 3 CE: -0.699671381310042"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.699671381310042 bestIt: 3 CE: -0.699671381310042"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.699671381310042 bestIt: 3 CE: -0.699671381310042"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.699671381310042 bestIt: 3 CE: -0.699671381310042"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.699671381310042 bestIt: 3 CE: -0.699671381310042"</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 1.25100508279622  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.514027982934267 bestIt: 1 CE: 0.514027982934267 featOrth: 0.00692849880254373"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.327358597155468 bestIt: 2 CE: 0.327358597155468 featOrth: 0.00248067393830068"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.264915352804844 bestIt: 3 CE: 0.264915352804844 featOrth: 0.0013634782183022"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.216473728553893 bestIt: 4 CE: 0.216473728553893 featOrth: 0.000890674759991841"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.159083632983409 bestIt: 5 CE: 0.159083632983409 featOrth: 0.00097976607081642"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.126304831433459 bestIt: 6 CE: 0.126304831433459 featOrth: 0.000175185575262014"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.114862132223346 bestIt: 7 CE: 0.114862132223346 featOrth: 0.000125164873978373"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.110429855353278 bestIt: 8 CE: 0.110429855353278 featOrth: 0.000129327044572087"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.10739906647692 bestIt: 9 CE: 0.10739906647692 featOrth: 0.000141472777676223"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.10739906647692 bestIt: 9 CE: 0.10739906647692 featOrth: 0.000141472777676223"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.105072829520251 bestIt: 11 CE: 0.105072829520251 featOrth: 0.000139536233327845"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.103774701232792 bestIt: 12 CE: 0.103774701232792 featOrth: 0.000149632296226467"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.103178504029944 bestIt: 13 CE: 0.103178504029944 featOrth: 0.00013938720216067"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.102312799856269 bestIt: 14 CE: 0.102312799856269 featOrth: 0.000152899899868399"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0941503079444059 bestIt: 15 CE: 0.0941503079444059 featOrth: 1.74250002166697e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0365007504880447 bestIt: 16 CE: 0.0365007504880447 featOrth: 0.000311274066882648"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0331101396486694 bestIt: 17 CE: 0.0331101396486694 featOrth: 0.000302966199879289"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0251054247820067 bestIt: 18 CE: 0.0251054247820067 featOrth: 1.94625018766891e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0133508646628454 bestIt: 19 CE: 0.0133508646628454 featOrth: 2.21110258123983e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0131365797736936 bestIt: 20 CE: 0.0131365797736936 featOrth: 2.28409729638059e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0129566473474053 bestIt: 21 CE: 0.0129566473474053 featOrth: 2.11962197051789e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0128033438014653 bestIt: 22 CE: 0.0128033438014653 featOrth: 2.18559952519997e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0117061619283051 bestIt: 23 CE: 0.0117061619283051 featOrth: 7.1464097218465e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0115705715069178 bestIt: 24 CE: 0.0115705715069178 featOrth: 7.11770036455469e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0115705715069178 bestIt: 24 CE: 0.0115705715069178 featOrth: 7.11770036455469e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.0115705715069178 bestIt: 24 CE: 0.0115705715069178 featOrth: 7.11770036455469e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0115705715069178 bestIt: 24 CE: 0.0115705715069178 featOrth: 7.11770036455469e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0115705715069178 bestIt: 24 CE: 0.0115705715069178 featOrth: 7.11770036455469e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0115705715069178 bestIt: 24 CE: 0.0115705715069178 featOrth: 7.11770036455469e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0115705715069178 bestIt: 24 CE: 0.0115705715069178 featOrth: 7.11770036455469e-05"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "orthox10x10"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "10"    "10"   </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.256180683310025  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.465407716401814 bestIt: 1 CE: -0.465407716401814 featOrth: 0.0066425646269503"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.537501857328162 bestIt: 2 CE: -0.537501857328162 featOrth: 0.00028365057119385"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.537501857328162 bestIt: 2 CE: -0.442292145165349 featOrth: 0.000269056457875333"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.537501857328162 bestIt: 2 CE: -0.42429460596064 featOrth: 0.000421971795713696"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.537501857328162 bestIt: 2 CE: -0.392615604874938 featOrth: 0.00040748756366741"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.537501857328162 bestIt: 2 CE: -0.372372231135211 featOrth: 0.000393203887005634"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.537501857328162 bestIt: 2 CE: -0.367753153092248 featOrth: 0.000222603796305205"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.558077100389071 bestIt: 8 CE: -0.558077100389071 featOrth: 0.000462440983670348"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.739154926408476 bestIt: 9 CE: -0.739154926408476 featOrth: 0.000185041617106693"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.759510615583493 bestIt: 10 CE: -0.759510615583493 featOrth: 0.000183660720726942"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.759510615583493 bestIt: 10 CE: -0.759510615583493 featOrth: 0.000183660720726942"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.759510615583493 bestIt: 10 CE: -0.759510615583493 featOrth: 0.000183660720726942"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.759510615583493 bestIt: 10 CE: -0.759510615583493 featOrth: 0.000183660720726942"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.759510615583493 bestIt: 10 CE: -0.759510615583493 featOrth: 0.000183660720726942"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.816354437327203 bestIt: 15 CE: -0.816354437327203 featOrth: 0.000909296852959383"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: -0.81750961997173 bestIt: 16 CE: -0.81750961997173 featOrth: 0.000287704550075755"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: -0.81750961997173 bestIt: 16 CE: -0.81750961997173 featOrth: 0.000287704550075755"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: -0.81750961997173 bestIt: 16 CE: -0.81750961997173 featOrth: 0.000287704550075755"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: -0.81750961997173 bestIt: 16 CE: -0.81750961997173 featOrth: 0.000287704550075755"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: -0.81750961997173 bestIt: 16 CE: -0.81750961997173 featOrth: 0.000287704550075755"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: -0.81750961997173 bestIt: 16 CE: -0.81750961997173 featOrth: 0.000287704550075755"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: -0.81750961997173 bestIt: 16 CE: -0.81750961997173 featOrth: 0.000287704550075755"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "orthox10x10"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "10"    "10"   </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 1.25100508279622  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.509019261310871 bestIt: 1 CE: 0.509019261310871 featOrth: 0.00692849880254373"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.330384281744342 bestIt: 2 CE: 0.330384281744342 featOrth: 0.00112109779396875"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.286402365727442 bestIt: 3 CE: 0.286402365727442 featOrth: 0.00203974592411764"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.258721144208048 bestIt: 4 CE: 0.258721144208048 featOrth: 0.0006906717281927"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.198345910181631 bestIt: 5 CE: 0.198345910181631 featOrth: 0.00126701584681045"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.161924960057787 bestIt: 6 CE: 0.161924960057787 featOrth: 7.34922301591711e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0732600209579528 bestIt: 7 CE: 0.0732600209579528 featOrth: 0.000861585239982377"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0673021667663417 bestIt: 8 CE: 0.0673021667663417 featOrth: 0.000477925694164482"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0506605532717843 bestIt: 9 CE: 0.0506605532717843 featOrth: 0.000653269314637859"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0506605532717843 bestIt: 9 CE: 0.0506605532717843 featOrth: 0.000653269314637859"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0506605532717843 bestIt: 9 CE: 0.0506605532717843 featOrth: 0.000653269314637859"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0506605532717843 bestIt: 9 CE: 0.0506605532717843 featOrth: 0.000653269314637859"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0506605532717843 bestIt: 9 CE: 0.0506605532717843 featOrth: 0.000653269314637859"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0506605532717843 bestIt: 9 CE: 0.0506605532717843 featOrth: 0.000653269314637859"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0506605532717843 bestIt: 9 CE: 0.0506605532717843 featOrth: 0.000653269314637859"</span></span>
 <span><span class="co">#&gt; [1] "improvement"</span></span>
 <span><span class="co">#&gt;   nsimlr objectiver mixer ebber    optimus  constraint final_energy prescaling1</span></span>
-<span><span class="co">#&gt; 1      2        cca   pca  0.99 lineSearch orthox10x10     19.52797      robust</span></span>
+<span><span class="co">#&gt; 1      2 regression   pca  0.99 lineSearch orthox10x10     21.87964      robust</span></span>
 <span><span class="co">#&gt;      prescaling2 prescaling3 sparval1 sparval2 sparval3 positivity1 positivity2</span></span>
 <span><span class="co">#&gt; 1 centerAndScale          np      0.5      0.5      0.5    positive    positive</span></span>
 <span><span class="co">#&gt;   positivity3 perm     m1_m2     m1_m3     m2_m3</span></span>
-<span><span class="co">#&gt; 1    positive    0 0.7414637 0.6217357 0.6284296</span></span>
-<span><span class="co">#&gt;              PC1         PC2</span></span>
-<span><span class="co">#&gt; m3.1 0.028115931 0.000000000</span></span>
-<span><span class="co">#&gt; m3.2 0.007094071 0.000000000</span></span>
-<span><span class="co">#&gt; m3.3 0.029487447 0.000000000</span></span>
-<span><span class="co">#&gt; m3.4 0.008334188 0.000000000</span></span>
-<span><span class="co">#&gt; m3.5 0.009841182 0.006295204</span></span>
-<span><span class="co">#&gt; m3.6 0.000000000 0.026495010</span></span>
+<span><span class="co">#&gt; 1    positive    0 0.6567739 0.6931875 0.5575234</span></span>
+<span><span class="co">#&gt;               PC1          PC2</span></span>
+<span><span class="co">#&gt; m3.1 0.0202650462 0.0000000000</span></span>
+<span><span class="co">#&gt; m3.2 0.0005020628 0.0006891443</span></span>
+<span><span class="co">#&gt; m3.3 0.0387266543 0.0000000000</span></span>
+<span><span class="co">#&gt; m3.4 0.0009518526 0.0000000000</span></span>
+<span><span class="co">#&gt; m3.5 0.0058221297 0.0000000000</span></span>
+<span><span class="co">#&gt; m3.6 0.0000000000 0.0078944845</span></span>
+<span><span class="co">#&gt; i 40 ...[1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "orthox10x10"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "10"    "10"   </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.256180683310025  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.477932082629505 bestIt: 1 CE: -0.477932082629505 featOrth: 0.0066425646269503"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.633998187173758 bestIt: 2 CE: -0.633998187173758 featOrth: 0.000361977115124601"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.673768996635339 bestIt: 3 CE: -0.673768996635339 featOrth: 0.000842215036533655"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.673768996635339 bestIt: 3 CE: -0.673768996635339 featOrth: 0.000842215036533655"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.673768996635339 bestIt: 3 CE: -0.673768996635339 featOrth: 0.000842215036533655"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.673768996635339 bestIt: 3 CE: -0.673768996635339 featOrth: 0.000842215036533655"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.673768996635339 bestIt: 3 CE: -0.673768996635339 featOrth: 0.000842215036533655"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.673768996635339 bestIt: 3 CE: -0.673768996635339 featOrth: 0.000842215036533655"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.673768996635339 bestIt: 3 CE: -0.673768996635339 featOrth: 0.000842215036533655"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "orthox100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "100"   "1"    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 2.95034167724203 bestIt: 1 CE: 2.95034167724203 featOrth: 0.0163946985372949"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.769216615803176 bestIt: 2 CE: 0.769216615803175 featOrth: 0.000268359174936063"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.541699367725949 bestIt: 3 CE: 0.541699367725949 featOrth: 0.000282183538467853"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.405870832369189 bestIt: 4 CE: 0.405870832369189 featOrth: 0.000338672214283897"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.360585584389924 bestIt: 5 CE: 0.360585584389924 featOrth: 0.000444188642358596"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.304885226078119 bestIt: 6 CE: 0.304885226078119 featOrth: 0.000978382647569787"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.148291573362309 bestIt: 7 CE: 0.148291573362309 featOrth: 9.25928170963193e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.148291573362309 bestIt: 7 CE: 0.150129930963155 featOrth: 0.000115409033088143"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.144351670206666 bestIt: 9 CE: 0.144351670206666 featOrth: 0.000179130893076226"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.102968693938261 bestIt: 10 CE: 0.102968693938261 featOrth: 9.11925736459646e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0986341885985887 bestIt: 11 CE: 0.0986341885985887 featOrth: 0.000114964702539623"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0781987019146673 bestIt: 12 CE: 0.0781987019146673 featOrth: 6.29111727751405e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0673500752401035 bestIt: 13 CE: 0.0673500752401035 featOrth: 1.55937575589802e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0541915127880351 featOrth: 5.93100183710251e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0541915127880351 featOrth: 5.93100183710251e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0541915127880351 featOrth: 5.93100183710251e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0541915127880351 featOrth: 5.93100183710251e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0620162181950984 featOrth: 0.000106662537269936"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.061459729490666 featOrth: 9.61464364398933e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0561583241626296 featOrth: 7.16129374209092e-05"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "orthox100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "100"   "1"    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.14101645515242 bestIt: 1 CE: -0.14101645515242 featOrth: 0.00640834391062016"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.648722230291816 bestIt: 2 CE: -0.648722230291816 featOrth: 5.7786921439967e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.721457073616115 bestIt: 3 CE: -0.721457073616115 featOrth: 3.81254486071124e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.731162260727681 bestIt: 4 CE: -0.731162260727681 featOrth: 9.81375380350779e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.732084277709889 bestIt: 5 CE: -0.732084277709889 featOrth: 7.37113137950689e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.732084277709889 bestIt: 5 CE: -0.732084277709889 featOrth: 7.37113137950689e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.771308287813386 bestIt: 7 CE: -0.771308287813386 featOrth: 0.000138335274146522"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.771308287813386 bestIt: 7 CE: -0.770913065436555 featOrth: 0.000167806249688568"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.771308287813386 bestIt: 7 CE: -0.767774109363983 featOrth: 0.000155527800101953"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.771308287813386 bestIt: 7 CE: -0.767774109363983 featOrth: 0.000155527800101953"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.771308287813386 bestIt: 7 CE: -0.767774109363983 featOrth: 0.000155527800101953"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.771308287813386 bestIt: 7 CE: -0.767774109363983 featOrth: 0.000155527800101953"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.771308287813386 bestIt: 7 CE: -0.767774109363983 featOrth: 0.000155527800101953"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "orthox100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "100"   "1"    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 2.94995647674522 bestIt: 1 CE: 2.94995647674522 featOrth: 0.0163946985372949"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.997925166988487 bestIt: 2 CE: 0.997925166988487 featOrth: 6.24609541325397e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.556934606963116 bestIt: 3 CE: 0.556934606963116 featOrth: 0.000442037015974229"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.392168838060075 bestIt: 4 CE: 0.392168838060075 featOrth: 0.000446956651721334"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.340810725004325 bestIt: 5 CE: 0.340810725004325 featOrth: 0.000694543373273903"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.144208534476617 bestIt: 6 CE: 0.144208534476617 featOrth: 0.000624946316002499"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0931408914873477 bestIt: 7 CE: 0.0931408914873477 featOrth: 0.000108074451120859"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.087615657116941 bestIt: 8 CE: 0.087615657116941 featOrth: 0.000129951979897279"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0750777868983458 bestIt: 9 CE: 0.0750777868983458 featOrth: 7.24878603311522e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0746480482880224 bestIt: 10 CE: 0.0746480482880224 featOrth: 8.50468369489329e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0743544863644732 bestIt: 11 CE: 0.0743544863644732 featOrth: 4.78957134524552e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0743544863644732 bestIt: 11 CE: 0.0766141180417366 featOrth: 5.87092727352304e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0555687725790828 bestIt: 13 CE: 0.0555687725790828 featOrth: 2.09368128698822e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0555687725790828 bestIt: 13 CE: 0.0728700504886686 featOrth: 2.84737787851716e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.055253398962663 bestIt: 15 CE: 0.055253398962663 featOrth: 3.83833750727906e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0525815272961396 bestIt: 16 CE: 0.0525815272961396 featOrth: 3.99888374320143e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0525815272961396 bestIt: 16 CE: 0.0533784311625752 featOrth: 5.76741166722116e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0518714120441519 bestIt: 18 CE: 0.0518714120441519 featOrth: 4.14949785438992e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0357406678370034 bestIt: 19 CE: 0.0357406678370034 featOrth: 4.14423625249359e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0357406678370034 bestIt: 19 CE: 0.0473387030501485 featOrth: 5.21108947061863e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0290597174334167 bestIt: 21 CE: 0.0290597174334167 featOrth: 2.15008663478603e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0290597174334167 bestIt: 21 CE: 0.0343106749468609 featOrth: 2.52938735519811e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0267332707309009 bestIt: 23 CE: 0.0267332707309009 featOrth: 1.8942617819923e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0267332707309009 bestIt: 23 CE: 0.0301273632116497 featOrth: 2.28385739085729e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0257985248646174 bestIt: 25 CE: 0.0257985248646174 featOrth: 1.8947121082177e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.0257985248646174 bestIt: 25 CE: 0.0268161223572859 featOrth: 2.09579126700376e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0257985248646174 bestIt: 25 CE: 0.0262299055292056 featOrth: 1.57054914479576e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0257985248646174 bestIt: 25 CE: 0.0262299055292056 featOrth: 1.57054914479576e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0249288530931636 bestIt: 29 CE: 0.0249288530931636 featOrth: 1.74989507105344e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0249271218647585 bestIt: 30 CE: 0.0249271218647585 featOrth: 1.55167291117256e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0244788615256479 bestIt: 31 CE: 0.0244788615256479 featOrth: 1.62529012755742e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0244788615256479 bestIt: 31 CE: 0.0244788615256479 featOrth: 1.62529012755742e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.0244788615256479 bestIt: 31 CE: 0.0244788615256479 featOrth: 1.62529012755742e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.0244788615256479 bestIt: 31 CE: 0.0247652521050868 featOrth: 1.55689293865345e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0235797876390652 featOrth: 1.59629940836857e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 39 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 40 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 41 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "orthox100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "100"   "1"    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.168638634836663 bestIt: 1 CE: -0.168638634836663 featOrth: 0.00640834391062016"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.619802503073671 bestIt: 2 CE: -0.619802503073671 featOrth: 7.74882349878907e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.698172171482991 bestIt: 3 CE: -0.698172171482991 featOrth: 0.000533405685884374"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.698172171482991 bestIt: 3 CE: -0.698172171482991 featOrth: 0.000533405685884374"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.698172171482991 bestIt: 3 CE: -0.69695257665203 featOrth: 0.000563799670292911"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.709204010564402 bestIt: 6 CE: -0.709204010564402 featOrth: 5.93693787828618e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.724880543949305 bestIt: 7 CE: -0.724880543949305 featOrth: 0.000137576776203833"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.724880543949305 bestIt: 7 CE: -0.724880543949305 featOrth: 0.000137576776203833"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.828774116584519 bestIt: 9 CE: -0.828774116584519 featOrth: 0.000235872523827676"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.828774116584519 bestIt: 9 CE: -0.828774116584519 featOrth: 0.000235872523827676"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.828774116584519 bestIt: 9 CE: -0.828774116584519 featOrth: 0.000235872523827676"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.828774116584519 bestIt: 9 CE: -0.828774116584519 featOrth: 0.000235872523827676"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.828774116584519 bestIt: 9 CE: -0.828774116584519 featOrth: 0.000235872523827676"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.850082082679088 bestIt: 14 CE: -0.850082082679088 featOrth: 0.00026472865618674"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.852451739621434 bestIt: 15 CE: -0.852451739621434 featOrth: 0.000238324844306358"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: -0.85612269690799 bestIt: 16 CE: -0.85612269690799 featOrth: 0.000167181323443809"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: -0.868751704513849 bestIt: 17 CE: -0.868751704513849 featOrth: 0.000222980490671906"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: -0.868751704513849 bestIt: 17 CE: -0.868751704513849 featOrth: 0.000222980490671906"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: -0.873550462882535 bestIt: 19 CE: -0.873550462882535 featOrth: 0.000222096908186005"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: -0.873550462882535 bestIt: 19 CE: -0.870198675526501 featOrth: 0.000186436315982429"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: -0.873550462882535 bestIt: 19 CE: -0.870198675526501 featOrth: 0.000186436315982429"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: -0.873550462882535 bestIt: 19 CE: -0.870198675526501 featOrth: 0.000186436315982429"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: -0.873550462882535 bestIt: 19 CE: -0.870198675526501 featOrth: 0.000186436315982429"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: -0.873550462882535 bestIt: 19 CE: -0.87252183102159 featOrth: 0.000192769330383968"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "orthox100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "100"   "1"    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 2.95034167724203 bestIt: 1 CE: 2.95034167724203 featOrth: 0.0163946985372949"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.769216615803176 bestIt: 2 CE: 0.769216615803175 featOrth: 0.000268359174936063"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.541699367725949 bestIt: 3 CE: 0.541699367725949 featOrth: 0.000282183538467853"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.405870832369189 bestIt: 4 CE: 0.405870832369189 featOrth: 0.000338672214283897"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.360585584389924 bestIt: 5 CE: 0.360585584389924 featOrth: 0.000444188642358596"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.304885226078119 bestIt: 6 CE: 0.304885226078119 featOrth: 0.000978382647569787"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.148291573362309 bestIt: 7 CE: 0.148291573362309 featOrth: 9.25928170963193e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.148291573362309 bestIt: 7 CE: 0.150129930963155 featOrth: 0.000115409033088143"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.144351670206666 bestIt: 9 CE: 0.144351670206666 featOrth: 0.000179130893076226"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.102968693938261 bestIt: 10 CE: 0.102968693938261 featOrth: 9.11925736459646e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0986341885985887 bestIt: 11 CE: 0.0986341885985887 featOrth: 0.000114964702539623"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0781987019146673 bestIt: 12 CE: 0.0781987019146673 featOrth: 6.29111727751405e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0673500752401035 bestIt: 13 CE: 0.0673500752401035 featOrth: 1.55937575589802e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0541915127880351 featOrth: 5.93100183710251e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0541915127880351 featOrth: 5.93100183710251e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0541915127880351 featOrth: 5.93100183710251e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0541915127880351 featOrth: 5.93100183710251e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0620162181950984 featOrth: 0.000106662537269936"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.061459729490666 featOrth: 9.61464364398933e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0541915127880351 bestIt: 14 CE: 0.0561583241626296 featOrth: 7.16129374209092e-05"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "orthox100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "100"   "1"    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.14101645515242 bestIt: 1 CE: -0.14101645515242 featOrth: 0.00640834391062016"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.648722230291816 bestIt: 2 CE: -0.648722230291816 featOrth: 5.7786921439967e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.721457073616115 bestIt: 3 CE: -0.721457073616115 featOrth: 3.81254486071124e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.731162260727681 bestIt: 4 CE: -0.731162260727681 featOrth: 9.81375380350779e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.732084277709889 bestIt: 5 CE: -0.732084277709889 featOrth: 7.37113137950689e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.732084277709889 bestIt: 5 CE: -0.732084277709889 featOrth: 7.37113137950689e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.771308287813386 bestIt: 7 CE: -0.771308287813386 featOrth: 0.000138335274146522"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.771308287813386 bestIt: 7 CE: -0.770913065436555 featOrth: 0.000167806249688568"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.771308287813386 bestIt: 7 CE: -0.767774109363983 featOrth: 0.000155527800101953"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.771308287813386 bestIt: 7 CE: -0.767774109363983 featOrth: 0.000155527800101953"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.771308287813386 bestIt: 7 CE: -0.767774109363983 featOrth: 0.000155527800101953"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.771308287813386 bestIt: 7 CE: -0.767774109363983 featOrth: 0.000155527800101953"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.771308287813386 bestIt: 7 CE: -0.767774109363983 featOrth: 0.000155527800101953"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "orthox100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "100"   "1"    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 7.25946837430251  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 2.94995647674522 bestIt: 1 CE: 2.94995647674522 featOrth: 0.0163946985372949"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.997925166988487 bestIt: 2 CE: 0.997925166988487 featOrth: 6.24609541325397e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.556934606963116 bestIt: 3 CE: 0.556934606963116 featOrth: 0.000442037015974229"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.392168838060075 bestIt: 4 CE: 0.392168838060075 featOrth: 0.000446956651721334"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.340810725004325 bestIt: 5 CE: 0.340810725004325 featOrth: 0.000694543373273903"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.144208534476617 bestIt: 6 CE: 0.144208534476617 featOrth: 0.000624946316002499"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0931408914873477 bestIt: 7 CE: 0.0931408914873477 featOrth: 0.000108074451120859"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.087615657116941 bestIt: 8 CE: 0.087615657116941 featOrth: 0.000129951979897279"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0750777868983458 bestIt: 9 CE: 0.0750777868983458 featOrth: 7.24878603311522e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0746480482880224 bestIt: 10 CE: 0.0746480482880224 featOrth: 8.50468369489329e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0743544863644732 bestIt: 11 CE: 0.0743544863644732 featOrth: 4.78957134524552e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0743544863644732 bestIt: 11 CE: 0.0766141180417366 featOrth: 5.87092727352304e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0555687725790828 bestIt: 13 CE: 0.0555687725790828 featOrth: 2.09368128698822e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0555687725790828 bestIt: 13 CE: 0.0728700504886686 featOrth: 2.84737787851716e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.055253398962663 bestIt: 15 CE: 0.055253398962663 featOrth: 3.83833750727906e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0525815272961396 bestIt: 16 CE: 0.0525815272961396 featOrth: 3.99888374320143e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0525815272961396 bestIt: 16 CE: 0.0533784311625752 featOrth: 5.76741166722116e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.0518714120441519 bestIt: 18 CE: 0.0518714120441519 featOrth: 4.14949785438992e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.0357406678370034 bestIt: 19 CE: 0.0357406678370034 featOrth: 4.14423625249359e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.0357406678370034 bestIt: 19 CE: 0.0473387030501485 featOrth: 5.21108947061863e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.0290597174334167 bestIt: 21 CE: 0.0290597174334167 featOrth: 2.15008663478603e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.0290597174334167 bestIt: 21 CE: 0.0343106749468609 featOrth: 2.52938735519811e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.0267332707309009 bestIt: 23 CE: 0.0267332707309009 featOrth: 1.8942617819923e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.0267332707309009 bestIt: 23 CE: 0.0301273632116497 featOrth: 2.28385739085729e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.0257985248646174 bestIt: 25 CE: 0.0257985248646174 featOrth: 1.8947121082177e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.0257985248646174 bestIt: 25 CE: 0.0268161223572859 featOrth: 2.09579126700376e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.0257985248646174 bestIt: 25 CE: 0.0262299055292056 featOrth: 1.57054914479576e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.0257985248646174 bestIt: 25 CE: 0.0262299055292056 featOrth: 1.57054914479576e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.0249288530931636 bestIt: 29 CE: 0.0249288530931636 featOrth: 1.74989507105344e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.0249271218647585 bestIt: 30 CE: 0.0249271218647585 featOrth: 1.55167291117256e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.0244788615256479 bestIt: 31 CE: 0.0244788615256479 featOrth: 1.62529012755742e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.0244788615256479 bestIt: 31 CE: 0.0244788615256479 featOrth: 1.62529012755742e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.0244788615256479 bestIt: 31 CE: 0.0244788615256479 featOrth: 1.62529012755742e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.0244788615256479 bestIt: 31 CE: 0.0247652521050868 featOrth: 1.55689293865345e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0235797876390652 featOrth: 1.59629940836857e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 38 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 39 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 40 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 41 bestEv: 0.0235797876390652 bestIt: 35 CE: 0.0263862673811576 featOrth: 1.68983991801221e-05"</span></span>
 <span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
 <span><span class="co">#&gt; [1] "cca"</span></span>
 <span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "orthox100x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "100"   "1"    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 5.75228260819627  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.168638634836663 bestIt: 1 CE: -0.168638634836663 featOrth: 0.00640834391062016"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.619802503073671 bestIt: 2 CE: -0.619802503073671 featOrth: 7.74882349878907e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.698172171482991 bestIt: 3 CE: -0.698172171482991 featOrth: 0.000533405685884374"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.698172171482991 bestIt: 3 CE: -0.698172171482991 featOrth: 0.000533405685884374"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.698172171482991 bestIt: 3 CE: -0.69695257665203 featOrth: 0.000563799670292911"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.709204010564402 bestIt: 6 CE: -0.709204010564402 featOrth: 5.93693787828618e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.724880543949305 bestIt: 7 CE: -0.724880543949305 featOrth: 0.000137576776203833"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.724880543949305 bestIt: 7 CE: -0.724880543949305 featOrth: 0.000137576776203833"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.828774116584519 bestIt: 9 CE: -0.828774116584519 featOrth: 0.000235872523827676"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.828774116584519 bestIt: 9 CE: -0.828774116584519 featOrth: 0.000235872523827676"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: -0.828774116584519 bestIt: 9 CE: -0.828774116584519 featOrth: 0.000235872523827676"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: -0.828774116584519 bestIt: 9 CE: -0.828774116584519 featOrth: 0.000235872523827676"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: -0.828774116584519 bestIt: 9 CE: -0.828774116584519 featOrth: 0.000235872523827676"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: -0.850082082679088 bestIt: 14 CE: -0.850082082679088 featOrth: 0.00026472865618674"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: -0.852451739621434 bestIt: 15 CE: -0.852451739621434 featOrth: 0.000238324844306358"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: -0.85612269690799 bestIt: 16 CE: -0.85612269690799 featOrth: 0.000167181323443809"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: -0.868751704513849 bestIt: 17 CE: -0.868751704513849 featOrth: 0.000222980490671906"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: -0.868751704513849 bestIt: 17 CE: -0.868751704513849 featOrth: 0.000222980490671906"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: -0.873550462882535 bestIt: 19 CE: -0.873550462882535 featOrth: 0.000222096908186005"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: -0.873550462882535 bestIt: 19 CE: -0.870198675526501 featOrth: 0.000186436315982429"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: -0.873550462882535 bestIt: 19 CE: -0.870198675526501 featOrth: 0.000186436315982429"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: -0.873550462882535 bestIt: 19 CE: -0.870198675526501 featOrth: 0.000186436315982429"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: -0.873550462882535 bestIt: 19 CE: -0.870198675526501 featOrth: 0.000186436315982429"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: -0.873550462882535 bestIt: 19 CE: -0.87252183102159 featOrth: 0.000192769330383968"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: -0.874065134780041 bestIt: 25 CE: -0.874065134780041 featOrth: 0.000201858246153632"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
 <span><span class="co">#&gt; [1] "orthox1x1"</span></span>
 <span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
 <span><span class="co">#&gt; [1] 0.99</span></span>
@@ -894,53 +2553,173 @@ <h3 id="evaluating-machine-learning-objective-functions">Evaluating Machine Lear
 <span><span class="co">#&gt; [1] "lineSearch"</span></span>
 <span><span class="co">#&gt; [1] "ortho" "1"     "1"    </span></span>
 <span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
-<span><span class="co">#&gt; [1] "initialDataTerm: -0.857027012460654  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.640608661063987 bestIt: 1 CE: -0.640608661063987"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.811112716679046 bestIt: 2 CE: -0.811112716679046"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.811112716679046 bestIt: 2 CE: -0.811112716679046"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.811112716679046 bestIt: 2 CE: -0.811112716679046"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.811112716679046 bestIt: 2 CE: -0.811112716679046"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.811112716679046 bestIt: 2 CE: -0.811112716679046"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.811112716679046 bestIt: 2 CE: -0.811112716679046"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.811112716679046 bestIt: 2 CE: -0.811112716679046"</span></span>
-<span><span class="co">#&gt; i 10 ...[1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 0.650158753645586  &lt;o&gt; mixer: ica  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.467852444044148 bestIt: 1 CE: 0.467852444044148 featOrth: 0.013213851122536"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.336389981114533 bestIt: 2 CE: 0.336389981114533 featOrth: 0.0386552762888785"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.226214945983412 bestIt: 3 CE: 0.226214945983412 featOrth: 1.0884567012559e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.0678519611954239 bestIt: 4 CE: 0.0678519611954239 featOrth: 0.0125218310543094"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.0441423745236251 bestIt: 5 CE: 0.0441423745236251 featOrth: 0.000409702579829544"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.0323785844121358 bestIt: 6 CE: 0.0323785844121358 featOrth: 0.0011550938354451"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0264457197425088 bestIt: 7 CE: 0.0264457197425088 featOrth: 0.00127547592525522"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0215490388123224 bestIt: 8 CE: 0.0215490388123224 featOrth: 0.000368738761953007"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.0192357950173879 bestIt: 9 CE: 0.0192357950173879 featOrth: 0.000551048665436415"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.0180345891541333 bestIt: 10 CE: 0.0180345891541333 featOrth: 0.000492290751139232"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0161956838359995 bestIt: 11 CE: 0.0161956838359995 featOrth: 0.000278712596851147"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0142393139668988 bestIt: 12 CE: 0.0142393139668988 featOrth: 0.000287806086256548"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.012901187755853 bestIt: 13 CE: 0.012901187755853 featOrth: 0.000126285510706182"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.00971301965447227 bestIt: 14 CE: 0.00971301965447227 featOrth: 0.000168974049216395"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.00928227761025762 bestIt: 15 CE: 0.00928227761025762 featOrth: 9.80188518386488e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.00892552150227574 bestIt: 16 CE: 0.00892552150227574 featOrth: 1.72847815047191e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.00871901971728851 bestIt: 17 CE: 0.00871901971728851 featOrth: 2.80283463488235e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 18 bestEv: 0.00871901971728851 bestIt: 17 CE: 0.00885778972858955 featOrth: 4.53870842394719e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 19 bestEv: 0.00841179242699247 bestIt: 19 CE: 0.00841179242699246 featOrth: 2.35566654803082e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 20 bestEv: 0.00835419207067815 bestIt: 20 CE: 0.00835419207067815 featOrth: 2.71963274130283e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 21 bestEv: 0.00826781653523584 bestIt: 21 CE: 0.00826781653523584 featOrth: 1.79853134255707e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 22 bestEv: 0.00821872375291515 bestIt: 22 CE: 0.00821872375291515 featOrth: 3.34202330220907e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 23 bestEv: 0.00820777412882035 bestIt: 23 CE: 0.00820777412882035 featOrth: 2.75756107425122e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 24 bestEv: 0.00818469319842176 bestIt: 24 CE: 0.00818469319842176 featOrth: 1.5423779623334e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 25 bestEv: 0.00818029380925995 bestIt: 25 CE: 0.00818029380925995 featOrth: 2.53996584832653e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 26 bestEv: 0.00815356249981097 bestIt: 26 CE: 0.00815356249981097 featOrth: 1.53418940593878e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 27 bestEv: 0.00814919868389826 bestIt: 27 CE: 0.00814919868389826 featOrth: 2.54021308474313e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 28 bestEv: 0.00812951603241134 bestIt: 28 CE: 0.00812951603241133 featOrth: 1.98714625032446e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 29 bestEv: 0.00810792585675206 bestIt: 29 CE: 0.00810792585675206 featOrth: 2.48234120507447e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 30 bestEv: 0.00810792585675206 bestIt: 29 CE: 0.00811341744551268 featOrth: 2.04532794349318e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 31 bestEv: 0.00810620029251445 bestIt: 31 CE: 0.00810620029251445 featOrth: 2.43818080180929e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 32 bestEv: 0.00810620029251445 bestIt: 31 CE: 0.00811969931865594 featOrth: 1.66099030274961e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 33 bestEv: 0.00810620029251445 bestIt: 31 CE: 0.00813189362884503 featOrth: 1.14737707686837e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 34 bestEv: 0.00810620029251445 bestIt: 31 CE: 0.00812174506249976 featOrth: 1.52296320339252e-05"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 35 bestEv: 0.00810620029251445 bestIt: 31 CE: 0.00813937377233017 featOrth: 9.45289049264615e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 36 bestEv: 0.00810620029251445 bestIt: 31 CE: 0.00814188077883499 featOrth: 9.67565271150072e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 37 bestEv: 0.00810620029251445 bestIt: 31 CE: 0.00814188077883499 featOrth: 9.67565271150072e-06"</span></span>
+<span><span class="co">#&gt; i 50 ...[1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "cca"</span></span>
+<span><span class="co">#&gt; [1] "ica"</span></span>
+<span><span class="co">#&gt; [1] "orthox1x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "1"     "1"    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.857027012460654  &lt;o&gt; mixer: ica  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.590323129664448 bestIt: 1 CE: -0.590323129664448 featOrth: 0.0691637811877302"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.691759030822687 bestIt: 2 CE: -0.691759030822688 featOrth: 0.0131574639834821"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.704093946126041 bestIt: 3 CE: -0.704093946126041 featOrth: 0.0121784507404034"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.830202638495802 bestIt: 4 CE: -0.830202638495802 featOrth: 0.013511453392068"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.830202638495802 bestIt: 4 CE: -0.828858072575535 featOrth: 0.012119758140752"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.830202638495802 bestIt: 4 CE: -0.828858072575535 featOrth: 0.012119758140752"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.830202638495802 bestIt: 4 CE: -0.828858072575535 featOrth: 0.012119758140752"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.830202638495802 bestIt: 4 CE: -0.828858072575535 featOrth: 0.012119758140752"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: -0.830202638495802 bestIt: 4 CE: -0.828858072575535 featOrth: 0.012119758140752"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: -0.830202638495802 bestIt: 4 CE: -0.828858072575535 featOrth: 0.012119758140752"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
+<span><span class="co">#&gt; [1] "regression"</span></span>
+<span><span class="co">#&gt; [1] "pca"</span></span>
+<span><span class="co">#&gt; [1] "orthox1x1"</span></span>
+<span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
+<span><span class="co">#&gt; [1] 0.99</span></span>
+<span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
+<span><span class="co">#&gt; [1] "lineSearch"</span></span>
+<span><span class="co">#&gt; [1] "ortho" "1"     "1"    </span></span>
+<span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: 0.650158753645586  &lt;o&gt; mixer: pca  &lt;o&gt; E:  regression"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: 0.462934744269136 bestIt: 1 CE: 0.462934744269136 featOrth: 0.013213851122536"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: 0.334549775715385 bestIt: 2 CE: 0.334549775715385 featOrth: 0.0358284173172784"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: 0.225281415258604 bestIt: 3 CE: 0.225281415258604 featOrth: 1.02539398611884e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: 0.067991166095238 bestIt: 4 CE: 0.067991166095238 featOrth: 0.0131101960990941"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: 0.0380797933734452 bestIt: 5 CE: 0.0380797933734452 featOrth: 5.38021816328619e-06"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: 0.0236101337700458 bestIt: 6 CE: 0.0236101337700458 featOrth: 0.00109046435358623"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: 0.0197055496517417 bestIt: 7 CE: 0.0197055496517417 featOrth: 0.000142702919188393"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: 0.0193242645663545 bestIt: 8 CE: 0.0193242645663545 featOrth: 0.000276759174726005"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 9 bestEv: 0.018419871024493 bestIt: 9 CE: 0.018419871024493 featOrth: 0.000172475345458029"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 10 bestEv: 0.016763412540775 bestIt: 10 CE: 0.016763412540775 featOrth: 0.000168956811504118"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 11 bestEv: 0.0164702794958271 bestIt: 11 CE: 0.0164702794958271 featOrth: 0.000192172557575361"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 12 bestEv: 0.0164702794958271 bestIt: 11 CE: 0.0169024951169734 featOrth: 0.000188603848740847"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 13 bestEv: 0.0164702794958271 bestIt: 11 CE: 0.0169024951169734 featOrth: 0.000188603848740847"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 14 bestEv: 0.0164702794958271 bestIt: 11 CE: 0.0168030955961183 featOrth: 0.000172098297442111"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 15 bestEv: 0.0164702794958271 bestIt: 11 CE: 0.0165793859531814 featOrth: 0.000168463039459764"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 16 bestEv: 0.0164702794958271 bestIt: 11 CE: 0.0165793859531814 featOrth: 0.000168463039459764"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 17 bestEv: 0.0164702794958271 bestIt: 11 CE: 0.0165666244653662 featOrth: 0.000166183152450804"</span></span>
+<span><span class="co">#&gt; [1] "robust"         "centerAndScale" "np"            </span></span>
 <span><span class="co">#&gt; [1] "cca"</span></span>
 <span><span class="co">#&gt; [1] "pca"</span></span>
-<span><span class="co">#&gt; [1] "orthox0.1x0.1"</span></span>
+<span><span class="co">#&gt; [1] "orthox1x1"</span></span>
 <span><span class="co">#&gt; [1] 0.5 0.5 0.5</span></span>
 <span><span class="co">#&gt; [1] 0.99</span></span>
 <span><span class="co">#&gt; [1] "positive" "positive" "positive"</span></span>
 <span><span class="co">#&gt; [1] "lineSearch"</span></span>
-<span><span class="co">#&gt; [1] "ortho" "0.1"   "0.1"  </span></span>
+<span><span class="co">#&gt; [1] "ortho" "1"     "1"    </span></span>
 <span><span class="co">#&gt; [1] "     &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt; BUILD-V &lt;0&gt;    "</span></span>
-<span><span class="co">#&gt; [1] "initialDataTerm: -0.917111645375717  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.493782414451495 bestIt: 1 CE: -0.493782414451495"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.885838987144042 bestIt: 2 CE: -0.885838987144042"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.885838987144042 bestIt: 2 CE: -0.881313228930842"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.885838987144042 bestIt: 2 CE: -0.881313228930842"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.885838987144042 bestIt: 2 CE: -0.84565784966314"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.885838987144042 bestIt: 2 CE: -0.834104933282779"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.885838987144042 bestIt: 2 CE: -0.817884633342666"</span></span>
-<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.885838987144042 bestIt: 2 CE: -0.825852104773952"</span></span>
-<span><span class="co">#&gt;   nsimlr objectiver mixer ebber    optimus  constraint final_energy prescaling1</span></span>
-<span><span class="co">#&gt; 8      2        cca   pca  0.99 lineSearch orthox10x10     19.52797      robust</span></span>
-<span><span class="co">#&gt;      prescaling2 prescaling3 sparval1 sparval2 sparval3 positivity1 positivity2</span></span>
-<span><span class="co">#&gt; 8 centerAndScale          np      0.5      0.5      0.5    positive    positive</span></span>
-<span><span class="co">#&gt;   positivity3 perm     m1_m2     m1_m3     m2_m3</span></span>
-<span><span class="co">#&gt; 8    positive    0 0.7414637 0.6217357 0.6284296</span></span>
+<span><span class="co">#&gt; [1] "initialDataTerm: -0.857027012460654  &lt;o&gt; mixer: pca  &lt;o&gt; E:  cca"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 1 bestEv: -0.628055477329717 bestIt: 1 CE: -0.628055477329717 featOrth: 0.0691637811877302"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 2 bestEv: -0.68341124162279 bestIt: 2 CE: -0.68341124162279 featOrth: 0.0126998420387586"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 3 bestEv: -0.68341124162279 bestIt: 2 CE: -0.683411241622789 featOrth: 0.0126998420387586"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 4 bestEv: -0.68341124162279 bestIt: 2 CE: -0.683411241622789 featOrth: 0.0126998420387586"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 5 bestEv: -0.68341124162279 bestIt: 2 CE: -0.683411241622789 featOrth: 0.0126998420387586"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 6 bestEv: -0.68341124162279 bestIt: 2 CE: -0.683411241622789 featOrth: 0.0126998420387586"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 7 bestEv: -0.68341124162279 bestIt: 2 CE: -0.683411241622789 featOrth: 0.0126998420387586"</span></span>
+<span><span class="co">#&gt; [1] "Iteration: 8 bestEv: -0.68341124162279 bestIt: 2 CE: -0.683411241622789 featOrth: 0.0126998420387586"</span></span>
+<span><span class="co">#&gt;    nsimlr objectiver mixer ebber    optimus  constraint final_energy</span></span>
+<span><span class="co">#&gt; 39      2 regression   pca  0.99 lineSearch orthox10x10     21.87964</span></span>
+<span><span class="co">#&gt;    prescaling1    prescaling2 prescaling3 sparval1 sparval2 sparval3</span></span>
+<span><span class="co">#&gt; 39      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt;    positivity1 positivity2 positivity3 perm     m1_m2     m1_m3     m2_m3</span></span>
+<span><span class="co">#&gt; 39    positive    positive    positive    0 0.6567739 0.6931875 0.5575234</span></span>
 <span><span class="co">#&gt; el finito</span></span>
 <span><span class="va">simlrXs</span><span class="op">$</span><span class="va">paramsearch</span></span>
-<span><span class="co">#&gt;    nsimlr objectiver mixer ebber    optimus        constraint final_energy</span></span>
-<span><span class="co">#&gt; 1       2        cca   pca  0.99 lineSearch              none     15.12304</span></span>
-<span><span class="co">#&gt; 2       2        cca   pca  0.99 lineSearch   Grassmannx10x10     14.68560</span></span>
-<span><span class="co">#&gt; 3       2        cca   pca  0.99 lineSearch     Grassmannx1x1     14.71550</span></span>
-<span><span class="co">#&gt; 4       2        cca   pca  0.99 lineSearch Grassmannx0.1x0.1     15.11430</span></span>
-<span><span class="co">#&gt; 5       2        cca   pca  0.99 lineSearch     Stiefelx10x10     15.98724</span></span>
-<span><span class="co">#&gt; 6       2        cca   pca  0.99 lineSearch       Stiefelx1x1     15.59972</span></span>
-<span><span class="co">#&gt; 7       2        cca   pca  0.99 lineSearch   Stiefelx0.1x0.1     14.93442</span></span>
-<span><span class="co">#&gt; 8       2        cca   pca  0.99 lineSearch       orthox10x10     19.52797</span></span>
-<span><span class="co">#&gt; 9       2        cca   pca  0.99 lineSearch         orthox1x1     18.50992</span></span>
-<span><span class="co">#&gt; 10      2        cca   pca  0.99 lineSearch     orthox0.1x0.1     14.78189</span></span>
+<span><span class="co">#&gt;    nsimlr objectiver mixer ebber    optimus      constraint final_energy</span></span>
+<span><span class="co">#&gt; 1       2 regression   ica  0.99 lineSearch            none     20.04116</span></span>
+<span><span class="co">#&gt; 2       2        cca   ica  0.99 lineSearch            none     15.74912</span></span>
+<span><span class="co">#&gt; 3       2 regression   pca  0.99 lineSearch            none     20.13228</span></span>
+<span><span class="co">#&gt; 4       2        cca   pca  0.99 lineSearch            none     14.56300</span></span>
+<span><span class="co">#&gt; 5       2 regression   ica  0.99 lineSearch Grassmannx10x10     21.56241</span></span>
+<span><span class="co">#&gt; 6       2        cca   ica  0.99 lineSearch Grassmannx10x10     14.20333</span></span>
+<span><span class="co">#&gt; 7       2 regression   pca  0.99 lineSearch Grassmannx10x10     18.62826</span></span>
+<span><span class="co">#&gt; 8       2        cca   pca  0.99 lineSearch Grassmannx10x10     13.29879</span></span>
+<span><span class="co">#&gt; 9       2 regression   ica  0.99 lineSearch Grassmannx100x1     20.27411</span></span>
+<span><span class="co">#&gt; 10      2        cca   ica  0.99 lineSearch Grassmannx100x1     16.30913</span></span>
+<span><span class="co">#&gt; 11      2 regression   pca  0.99 lineSearch Grassmannx100x1     19.84864</span></span>
+<span><span class="co">#&gt; 12      2        cca   pca  0.99 lineSearch Grassmannx100x1     15.46196</span></span>
+<span><span class="co">#&gt; 13      2 regression   ica  0.99 lineSearch Grassmannx100x1     20.27411</span></span>
+<span><span class="co">#&gt; 14      2        cca   ica  0.99 lineSearch Grassmannx100x1     16.30913</span></span>
+<span><span class="co">#&gt; 15      2 regression   pca  0.99 lineSearch Grassmannx100x1     19.84864</span></span>
+<span><span class="co">#&gt; 16      2        cca   pca  0.99 lineSearch Grassmannx100x1     15.46196</span></span>
+<span><span class="co">#&gt; 17      2 regression   ica  0.99 lineSearch   Grassmannx1x1     19.21324</span></span>
+<span><span class="co">#&gt; 18      2        cca   ica  0.99 lineSearch   Grassmannx1x1     15.25255</span></span>
+<span><span class="co">#&gt; 19      2 regression   pca  0.99 lineSearch   Grassmannx1x1     18.95521</span></span>
+<span><span class="co">#&gt; 20      2        cca   pca  0.99 lineSearch   Grassmannx1x1     14.80697</span></span>
+<span><span class="co">#&gt; 21      2 regression   ica  0.99 lineSearch   Stiefelx10x10     21.58253</span></span>
+<span><span class="co">#&gt; 22      2        cca   ica  0.99 lineSearch   Stiefelx10x10     13.58371</span></span>
+<span><span class="co">#&gt; 23      2 regression   pca  0.99 lineSearch   Stiefelx10x10     18.01854</span></span>
+<span><span class="co">#&gt; 24      2        cca   pca  0.99 lineSearch   Stiefelx10x10     14.74664</span></span>
+<span><span class="co">#&gt; 25      2 regression   ica  0.99 lineSearch   Stiefelx100x1     19.41960</span></span>
+<span><span class="co">#&gt; 26      2        cca   ica  0.99 lineSearch   Stiefelx100x1     16.41269</span></span>
+<span><span class="co">#&gt; 27      2 regression   pca  0.99 lineSearch   Stiefelx100x1     20.63528</span></span>
+<span><span class="co">#&gt; 28      2        cca   pca  0.99 lineSearch   Stiefelx100x1     13.57193</span></span>
+<span><span class="co">#&gt; 29      2 regression   ica  0.99 lineSearch   Stiefelx100x1     19.41960</span></span>
+<span><span class="co">#&gt; 30      2        cca   ica  0.99 lineSearch   Stiefelx100x1     16.41269</span></span>
+<span><span class="co">#&gt; 31      2 regression   pca  0.99 lineSearch   Stiefelx100x1     20.63528</span></span>
+<span><span class="co">#&gt; 32      2        cca   pca  0.99 lineSearch   Stiefelx100x1     13.57193</span></span>
+<span><span class="co">#&gt; 33      2 regression   ica  0.99 lineSearch     Stiefelx1x1     16.40009</span></span>
+<span><span class="co">#&gt; 34      2        cca   ica  0.99 lineSearch     Stiefelx1x1     15.55203</span></span>
+<span><span class="co">#&gt; 35      2 regression   pca  0.99 lineSearch     Stiefelx1x1     19.58717</span></span>
+<span><span class="co">#&gt; 36      2        cca   pca  0.99 lineSearch     Stiefelx1x1     15.53778</span></span>
+<span><span class="co">#&gt; 37      2 regression   ica  0.99 lineSearch     orthox10x10     19.31468</span></span>
+<span><span class="co">#&gt; 38      2        cca   ica  0.99 lineSearch     orthox10x10     19.48686</span></span>
+<span><span class="co">#&gt; 39      2 regression   pca  0.99 lineSearch     orthox10x10     21.87964</span></span>
+<span><span class="co">#&gt; 40      2        cca   pca  0.99 lineSearch     orthox10x10     20.59885</span></span>
+<span><span class="co">#&gt; 41      2 regression   ica  0.99 lineSearch     orthox100x1     20.95390</span></span>
+<span><span class="co">#&gt; 42      2        cca   ica  0.99 lineSearch     orthox100x1     15.53850</span></span>
+<span><span class="co">#&gt; 43      2 regression   pca  0.99 lineSearch     orthox100x1     19.60430</span></span>
+<span><span class="co">#&gt; 44      2        cca   pca  0.99 lineSearch     orthox100x1     16.79858</span></span>
+<span><span class="co">#&gt; 45      2 regression   ica  0.99 lineSearch     orthox100x1     20.95390</span></span>
+<span><span class="co">#&gt; 46      2        cca   ica  0.99 lineSearch     orthox100x1     15.53850</span></span>
+<span><span class="co">#&gt; 47      2 regression   pca  0.99 lineSearch     orthox100x1     19.60430</span></span>
+<span><span class="co">#&gt; 48      2        cca   pca  0.99 lineSearch     orthox100x1     16.79858</span></span>
+<span><span class="co">#&gt; 49      2 regression   ica  0.99 lineSearch       orthox1x1     16.66613</span></span>
+<span><span class="co">#&gt; 50      2        cca   ica  0.99 lineSearch       orthox1x1     17.64868</span></span>
+<span><span class="co">#&gt; 51      2 regression   pca  0.99 lineSearch       orthox1x1     16.59218</span></span>
+<span><span class="co">#&gt; 52      2        cca   pca  0.99 lineSearch       orthox1x1     16.61590</span></span>
 <span><span class="co">#&gt;    prescaling1    prescaling2 prescaling3 sparval1 sparval2 sparval3</span></span>
 <span><span class="co">#&gt; 1       robust centerAndScale          np      0.5      0.5      0.5</span></span>
 <span><span class="co">#&gt; 2       robust centerAndScale          np      0.5      0.5      0.5</span></span>
@@ -952,17 +2731,101 @@ <h3 id="evaluating-machine-learning-objective-functions">Evaluating Machine Lear
 <span><span class="co">#&gt; 8       robust centerAndScale          np      0.5      0.5      0.5</span></span>
 <span><span class="co">#&gt; 9       robust centerAndScale          np      0.5      0.5      0.5</span></span>
 <span><span class="co">#&gt; 10      robust centerAndScale          np      0.5      0.5      0.5</span></span>
-<span><span class="co">#&gt;    positivity1 positivity2 positivity3 perm     m1_m2     m1_m3     m2_m3</span></span>
-<span><span class="co">#&gt; 1     positive    positive    positive    0 0.3978730 0.4029476 0.4574523</span></span>
-<span><span class="co">#&gt; 2     positive    positive    positive    0 0.5983526 0.5704775 0.4275200</span></span>
-<span><span class="co">#&gt; 3     positive    positive    positive    0 0.4576600 0.4044627 0.4753633</span></span>
-<span><span class="co">#&gt; 4     positive    positive    positive    0 0.4413322 0.4500521 0.4091796</span></span>
-<span><span class="co">#&gt; 5     positive    positive    positive    0 0.7731677 0.4217462 0.4443339</span></span>
-<span><span class="co">#&gt; 6     positive    positive    positive    0 0.4954192 0.4415130 0.4643743</span></span>
-<span><span class="co">#&gt; 7     positive    positive    positive    0 0.4782384 0.4838122 0.4320946</span></span>
-<span><span class="co">#&gt; 8     positive    positive    positive    0 0.7414637 0.6217357 0.6284296</span></span>
-<span><span class="co">#&gt; 9     positive    positive    positive    0 0.6147825 0.3888984 0.4125018</span></span>
-<span><span class="co">#&gt; 10    positive    positive    positive    0 0.4978481 0.3309805 0.2496383</span></span></code></pre></div>
+<span><span class="co">#&gt; 11      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 12      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 13      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 14      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 15      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 16      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 17      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 18      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 19      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 20      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 21      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 22      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 23      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 24      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 25      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 26      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 27      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 28      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 29      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 30      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 31      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 32      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 33      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 34      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 35      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 36      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 37      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 38      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 39      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 40      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 41      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 42      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 43      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 44      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 45      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 46      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 47      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 48      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 49      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 50      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 51      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt; 52      robust centerAndScale          np      0.5      0.5      0.5</span></span>
+<span><span class="co">#&gt;    positivity1 positivity2 positivity3 perm     m1_m2     m1_m3      m2_m3</span></span>
+<span><span class="co">#&gt; 1     positive    positive    positive    0 0.5193438 0.3119511 0.32150538</span></span>
+<span><span class="co">#&gt; 2     positive    positive    positive    0 0.4933520 0.4642482 0.47783498</span></span>
+<span><span class="co">#&gt; 3     positive    positive    positive    0 0.5044138 0.2953116 0.30520248</span></span>
+<span><span class="co">#&gt; 4     positive    positive    positive    0 0.4967490 0.3854782 0.39717215</span></span>
+<span><span class="co">#&gt; 5     positive    positive    positive    0 0.6938846 0.3555743 0.43754104</span></span>
+<span><span class="co">#&gt; 6     positive    positive    positive    0 0.4832839 0.4543970 0.43024417</span></span>
+<span><span class="co">#&gt; 7     positive    positive    positive    0 0.2806490 0.2115659 0.46072887</span></span>
+<span><span class="co">#&gt; 8     positive    positive    positive    0 0.5983526 0.2817692 0.45230352</span></span>
+<span><span class="co">#&gt; 9     positive    positive    positive    0 0.3257290 0.5084995 0.39397241</span></span>
+<span><span class="co">#&gt; 10    positive    positive    positive    0 0.4592238 0.6887583 0.54211957</span></span>
+<span><span class="co">#&gt; 11    positive    positive    positive    0 0.4401356 0.3878720 0.32870526</span></span>
+<span><span class="co">#&gt; 12    positive    positive    positive    0 0.6652509 0.5737221 0.43181128</span></span>
+<span><span class="co">#&gt; 13    positive    positive    positive    0 0.3257290 0.5084995 0.39397241</span></span>
+<span><span class="co">#&gt; 14    positive    positive    positive    0 0.4592238 0.6887583 0.54211957</span></span>
+<span><span class="co">#&gt; 15    positive    positive    positive    0 0.4401356 0.3878720 0.32870526</span></span>
+<span><span class="co">#&gt; 16    positive    positive    positive    0 0.6652509 0.5737221 0.43181128</span></span>
+<span><span class="co">#&gt; 17    positive    positive    positive    0 0.4182959 0.2630673 0.27593023</span></span>
+<span><span class="co">#&gt; 18    positive    positive    positive    0 0.4400600 0.4192347 0.47939687</span></span>
+<span><span class="co">#&gt; 19    positive    positive    positive    0 0.4284390 0.2797991 0.28730667</span></span>
+<span><span class="co">#&gt; 20    positive    positive    positive    0 0.5072330 0.3971236 0.39494615</span></span>
+<span><span class="co">#&gt; 21    positive    positive    positive    0 0.6219873 0.6071353 0.64259492</span></span>
+<span><span class="co">#&gt; 22    positive    positive    positive    0 0.4591461 0.4386191 0.44878946</span></span>
+<span><span class="co">#&gt; 23    positive    positive    positive    0 0.2572217 0.1170560 0.43287251</span></span>
+<span><span class="co">#&gt; 24    positive    positive    positive    0 0.4622607 0.4812358 0.44982004</span></span>
+<span><span class="co">#&gt; 25    positive    positive    positive    0 0.2981088 0.4603660 0.38168717</span></span>
+<span><span class="co">#&gt; 26    positive    positive    positive    0 0.7387857 0.4531428 0.45871239</span></span>
+<span><span class="co">#&gt; 27    positive    positive    positive    0 0.3605560 0.6582374 0.41269322</span></span>
+<span><span class="co">#&gt; 28    positive    positive    positive    0 0.4209124 0.3366873 0.48837377</span></span>
+<span><span class="co">#&gt; 29    positive    positive    positive    0 0.2981088 0.4603660 0.38168717</span></span>
+<span><span class="co">#&gt; 30    positive    positive    positive    0 0.7387857 0.4531428 0.45871239</span></span>
+<span><span class="co">#&gt; 31    positive    positive    positive    0 0.3605560 0.6582374 0.41269322</span></span>
+<span><span class="co">#&gt; 32    positive    positive    positive    0 0.4209124 0.3366873 0.48837377</span></span>
+<span><span class="co">#&gt; 33    positive    positive    positive    0 0.2355616 0.1113608 0.25074309</span></span>
+<span><span class="co">#&gt; 34    positive    positive    positive    0 0.4467106 0.4368430 0.50110487</span></span>
+<span><span class="co">#&gt; 35    positive    positive    positive    0 0.4113251 0.3015637 0.34805995</span></span>
+<span><span class="co">#&gt; 36    positive    positive    positive    0 0.4752949 0.4448870 0.52104372</span></span>
+<span><span class="co">#&gt; 37    positive    positive    positive    0 0.4928138 0.3116463 0.22098611</span></span>
+<span><span class="co">#&gt; 38    positive    positive    positive    0 0.7795813 0.5640667 0.56157863</span></span>
+<span><span class="co">#&gt; 39    positive    positive    positive    0 0.6567739 0.6931875 0.55752340</span></span>
+<span><span class="co">#&gt; 40    positive    positive    positive    0 0.7842817 0.8446771 0.81882527</span></span>
+<span><span class="co">#&gt; 41    positive    positive    positive    0 0.3294659 0.7176200 0.41250854</span></span>
+<span><span class="co">#&gt; 42    positive    positive    positive    0 0.7756144 0.3085523 0.41735434</span></span>
+<span><span class="co">#&gt; 43    positive    positive    positive    0 0.3547808 0.6492641 0.29208830</span></span>
+<span><span class="co">#&gt; 44    positive    positive    positive    0 0.4925081 0.4390126 0.49335414</span></span>
+<span><span class="co">#&gt; 45    positive    positive    positive    0 0.3294659 0.7176200 0.41250854</span></span>
+<span><span class="co">#&gt; 46    positive    positive    positive    0 0.7756144 0.3085523 0.41735434</span></span>
+<span><span class="co">#&gt; 47    positive    positive    positive    0 0.3547808 0.6492641 0.29208830</span></span>
+<span><span class="co">#&gt; 48    positive    positive    positive    0 0.4925081 0.4390126 0.49335414</span></span>
+<span><span class="co">#&gt; 49    positive    positive    positive    0 0.4955356 0.1919714 0.15419681</span></span>
+<span><span class="co">#&gt; 50    positive    positive    positive    0 0.5537755 0.4467084 0.49017259</span></span>
+<span><span class="co">#&gt; 51    positive    positive    positive    0 0.4636090 0.2714441 0.04486653</span></span>
+<span><span class="co">#&gt; 52    positive    positive    positive    0 0.5537755 0.2789453 0.25469184</span></span></code></pre></div>
 <p>Finally, <code>simlrXs$paramsearch</code> retrieves the results of
 the parameter search. This will show the performance of different
 parameter combinations, helping to identify the optimal settings for the
diff --git a/docs/articles/simlr_interpretation_files/figure-html/dataintegration-1.png b/docs/articles/simlr_interpretation_files/figure-html/dataintegration-1.png
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diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index ad5be077..c3040238 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -8,5 +8,5 @@ articles:
   iMath: iMath.html
   multivarTemplateCoordinates: multivarTemplateCoordinates.html
   simlr_interpretation: simlr_interpretation.html
-last_built: 2024-08-13T12:24Z
+last_built: 2024-08-31T18:55Z
 
diff --git a/docs/reference/antsApplyTransforms.html b/docs/reference/antsApplyTransforms.html
index 6872e481..3d45d1e7 100644
--- a/docs/reference/antsApplyTransforms.html
+++ b/docs/reference/antsApplyTransforms.html
@@ -182,7 +182,7 @@ <h2>Examples</h2>
 <span class="r-in"><span>  fixed <span class="op">=</span> <span class="va">fixed</span>, moving <span class="op">=</span> <span class="va">moving</span>,</span></span>
 <span class="r-in"><span>  typeofTransform <span class="op">=</span> <span class="st">"SyN"</span>, verbose <span class="op">=</span> <span class="cn">TRUE</span>, printArgs <span class="op">=</span> <span class="cn">TRUE</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> antsRegistration -d 2 -r [0x6000010e9d70,0x6000010e9ea0,1] -m mattes[0x6000010e9d70,0x6000010e9ea0,1,32,regular,0.2] -t Affine[0.25] -c 2100x1200x1200x0 -s 3x2x1x0 -f 4x2x2x1 -x [NA,NA] -m mattes[0x6000010e9d70,0x6000010e9ea0,1,32] -t SyN[0.2,3,0] -c [ 40x20x0 ,1e-7,8] -s 2x1x0 -f 4x2x1 -u 0 -z 1 -o [/tmp//Rtmp5A3DVJ/filec1b51f078ea6,0x6000010e9e10,0x6000010ea0e0] -x [NA,NA] --float 1 --random-seed 1 --write-composite-transform 0 -v 1 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> antsRegistration -d 2 -r [0x6000022176c0,0x600002217120,1] -m mattes[0x6000022176c0,0x600002217120,1,32,regular,0.2] -t Affine[0.25] -c 2100x1200x1200x0 -s 3x2x1x0 -f 4x2x2x1 -x [NA,NA] -m mattes[0x6000022176c0,0x600002217120,1,32] -t SyN[0.2,3,0] -c [ 40x20x0 ,1e-7,8] -s 2x1x0 -f 4x2x1 -u 0 -z 1 -o [/tmp//RtmpqqMYeq/file51c5556fc85b,0x600002217080,0x600002217060] -x [NA,NA] --float 1 --random-seed 1 --write-composite-transform 0 -v 1 </span>
 <span class="r-in"><span><span class="va">mywarpedimage</span> <span class="op">&lt;-</span> <span class="fu">antsApplyTransforms</span><span class="op">(</span></span></span>
 <span class="r-in"><span>  fixed <span class="op">=</span> <span class="va">fixed</span>, moving <span class="op">=</span> <span class="va">moving</span>,</span></span>
 <span class="r-in"><span>  transformlist <span class="op">=</span> <span class="va">mytx</span><span class="op">$</span><span class="va">fwdtransforms</span></span></span>
@@ -203,15 +203,15 @@ <h2>Examples</h2>
 <span class="r-out co"><span class="r-pr">#&gt;</span>  [1] "-d"                                                     </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>  [2] "2"                                                      </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>  [3] "-i"                                                     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [4] "&lt;pointer: 0x6000010e9e70&gt;"                              </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [4] "&lt;pointer: 0x600002216da0&gt;"                              </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>  [5] "-o"                                                     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [6] "&lt;pointer: 0x6000010d5fc0&gt;"                              </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [6] "&lt;pointer: 0x600002216f90&gt;"                              </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>  [7] "-r"                                                     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [8] "&lt;pointer: 0x6000010bc000&gt;"                              </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [8] "&lt;pointer: 0x600002216ce0&gt;"                              </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>  [9] "-n"                                                     </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [10] "linear"                                                 </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [11] "-t"                                                     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [12] "[/tmp//Rtmp5A3DVJ/filec1b51f078ea60GenericAffine.mat,1]"</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [12] "[/tmp//RtmpqqMYeq/file51c5556fc85b0GenericAffine.mat,1]"</span>
 <span class="r-in"><span><span class="va">cfile</span> <span class="op">&lt;-</span> <span class="fu">antsApplyTransforms</span><span class="op">(</span></span></span>
 <span class="r-in"><span>  fixed <span class="op">=</span> <span class="va">fixed</span>, moving <span class="op">=</span> <span class="va">moving</span>,</span></span>
 <span class="r-in"><span>  transformlist <span class="op">=</span> <span class="va">mytx</span><span class="op">$</span><span class="va">fwdtransforms</span>,</span></span>
diff --git a/docs/reference/antspymm_simlr.html b/docs/reference/antspymm_simlr.html
index 35c395cb..606270fc 100644
--- a/docs/reference/antspymm_simlr.html
+++ b/docs/reference/antspymm_simlr.html
@@ -79,8 +79,9 @@ <h1>Perform SiMLR Analysis on Multimodal ANTsPyMM Data</h1>
 <span>  <span class="va">blaster</span>,</span>
 <span>  <span class="va">select_training_boolean</span>,</span>
 <span>  <span class="va">connect_cog</span>,</span>
-<span>  energy <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"cca"</span>, <span class="st">"reg"</span>, <span class="st">"lrr"</span><span class="op">)</span>,</span>
-<span>  nsimlr <span class="op">=</span> <span class="fl">5</span>,</span>
+<span>  energy <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"cca"</span>, <span class="st">"reg"</span>, <span class="st">"lrr"</span>, <span class="st">"regression"</span><span class="op">)</span>,</span>
+<span>  <span class="va">nsimlr</span>,</span>
+<span>  <span class="va">constraint</span>,</span>
 <span>  covariates <span class="op">=</span> <span class="st">"1"</span>,</span>
 <span>  myseed <span class="op">=</span> <span class="fl">3</span>,</span>
 <span>  doAsym <span class="op">=</span> <span class="cn">TRUE</span>,</span>
@@ -92,6 +93,7 @@ <h1>Perform SiMLR Analysis on Multimodal ANTsPyMM Data</h1>
 <span>  inclusions <span class="op">=</span> <span class="cn">NULL</span>,</span>
 <span>  sparseness <span class="op">=</span> <span class="cn">NULL</span>,</span>
 <span>  iterations <span class="op">=</span> <span class="cn">NULL</span>,</span>
+<span>  path_modeling <span class="op">=</span> <span class="cn">NULL</span>,</span>
 <span>  verbose <span class="op">=</span> <span class="cn">FALSE</span></span>
 <span><span class="op">)</span></span></code></pre></div>
     </div>
@@ -118,6 +120,10 @@ <h2>Arguments</h2>
 <dd><p>Number of components.</p></dd>
 
 
+<dt>constraint</dt>
+<dd><p>orthogonality constraint of the form constraintxFloatWeightEnergyxFloatWeightGrad where constraints is ortho, Stiefel or Grassmann or GrassmannInv</p></dd>
+
+
 <dt>covariates</dt>
 <dd><p>any covariates to adjust training matrices. if covariates is set to 'mean' then the rowwise mean will be factored out of each matrix.  this can be a vector e.g. <code>c('center','scale','rank')</code>. pass the name opt to antspymm_simlr_update_residuals to have the function print the options.</p></dd>
 
@@ -162,6 +168,10 @@ <h2>Arguments</h2>
 <dd><p>int value to set max iterations</p></dd>
 
 
+<dt>path_modeling</dt>
+<dd><p>the result of a call to <code>simlr_path_models(n)</code></p></dd>
+
+
 <dt>verbose</dt>
 <dd><p>boolean</p></dd>
 
diff --git a/docs/reference/antsrGetPointerName.html b/docs/reference/antsrGetPointerName.html
index 5cfd4656..e6b7dee0 100644
--- a/docs/reference/antsrGetPointerName.html
+++ b/docs/reference/antsrGetPointerName.html
@@ -96,9 +96,9 @@ <h2>Examples</h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="va">img</span> <span class="op">&lt;-</span> <span class="fu"><a href="antsImageRead.html">antsImageRead</a></span><span class="op">(</span><span class="fu"><a href="getANTsRData.html">getANTsRData</a></span><span class="op">(</span><span class="st">"r16"</span><span class="op">)</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu">antsrGetPointerName</span><span class="op">(</span><span class="va">img</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "0x6000010dfd80"</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "0x60000221e450"</span>
 <span class="r-in"><span><span class="fu">antsrGetPointerName</span><span class="op">(</span><span class="fu"><a href="antsImageClone.html">antsImageClone</a></span><span class="op">(</span><span class="va">img</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "0x6000010dc3c0"</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "0x60000221f4f0"</span>
 <span class="r-in"><span></span></span>
 </code></pre></div>
     </div>
diff --git a/docs/reference/as.antsMatrix.html b/docs/reference/as.antsMatrix.html
index 99bdef27..f0b4d66a 100644
--- a/docs/reference/as.antsMatrix.html
+++ b/docs/reference/as.antsMatrix.html
@@ -104,7 +104,7 @@ <h2>Examples</h2>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "float"</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Slot "pointer":</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> &lt;pointer: 0x6000007d1c00&gt;</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> &lt;pointer: 0x6000035078c0&gt;</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-in"><span><span class="va">mat</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span>, nrow <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/as.data.frame.html" class="external-link">as.data.frame</a></span><span class="op">(</span><span class="va">mat</span><span class="op">)</span></span></span>
@@ -114,7 +114,7 @@ <h2>Examples</h2>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "float"</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Slot "pointer":</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> &lt;pointer: 0x6000007d3900&gt;</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> &lt;pointer: 0x600003506080&gt;</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-in"><span><span class="fu">as.antsMatrix</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">as.list</a></span><span class="op">(</span><span class="va">df</span><span class="op">)</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> An object of class "antsMatrix"</span>
@@ -122,7 +122,7 @@ <h2>Examples</h2>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "float"</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Slot "pointer":</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> &lt;pointer: 0x6000007d1f00&gt;</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> &lt;pointer: 0x600003507fc0&gt;</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 </code></pre></div>
     </div>
diff --git a/docs/reference/brackets.html b/docs/reference/brackets.html
index 6748911e..2230118d 100644
--- a/docs/reference/brackets.html
+++ b/docs/reference/brackets.html
@@ -119,58 +119,58 @@ <h1>Extract or Replace Parts of antsImage Object</h1>
 # S4 method for antsImage,missing,numeric,array
 [(x, i, j, ...) &lt;- value
 
-# S4 method for antsImage,NULL,ANY
+# S4 method for antsImage,NULL,ANY,ANY
 [(x, i, j, ..., drop = TRUE)
 
-# S4 method for antsImage,antsImage,ANY
+# S4 method for antsImage,antsImage,ANY,ANY
 [(x, i, j, ..., drop = TRUE)
 
-# S4 method for ANY,antsImage,ANY
+# S4 method for ANY,antsImage,ANY,ANY
 [(x, i, j, ..., drop = TRUE)
 
-# S4 method for antsImage,logical,ANY
+# S4 method for antsImage,logical,ANY,ANY
 [(x, i, j, ..., drop = TRUE)
 
-# S4 method for antsImage,logical,ANY
+# S4 method for antsImage,logical,ANY,ANY
 [(x, i, j, ..., drop = TRUE)
 
-# S4 method for antsImage,ANY,ANY
+# S4 method for antsImage,ANY,ANY,ANY
 [(x, i, j, ..., drop = TRUE)
 
-# S4 method for antsImage,ANY,ANY
+# S4 method for antsImage,ANY,ANY,ANY
 [(x, i, j, ..., drop = TRUE)
 
-# S4 method for antsImage,NULL,NULL
+# S4 method for antsImage,NULL,NULL,ANY
 [(x, i, j, k = NA, l = NA, ..., drop)
 
-# S4 method for antsImage,NULL,NULL
+# S4 method for antsImage,NULL,NULL,ANY
 [(x, i, j, k = NA, l = NA, ..., drop)
 
-# S4 method for antsImage,numeric,numeric
+# S4 method for antsImage,numeric,numeric,ANY
 [(x, i, j, k = NA, l = NA, ..., drop)
 
-# S4 method for antsImage,numeric,numeric
+# S4 method for antsImage,numeric,numeric,ANY
 [(x, i, j, k = NA, l = NA, ..., drop)
 
-# S4 method for antsImage,numeric,NULL
+# S4 method for antsImage,numeric,NULL,ANY
 [(x, i, j, k = NA, l = NA, ..., drop)
 
-# S4 method for antsImage,numeric,NULL
+# S4 method for antsImage,numeric,NULL,ANY
 [(x, i, j, k = NA, l = NA, ..., drop)
 
-# S4 method for antsImage,NULL,numeric
+# S4 method for antsImage,NULL,numeric,ANY
 [(x, i, j, k = NA, l = NA, ..., drop)
 
-# S4 method for antsImage,NULL,numeric
+# S4 method for antsImage,NULL,numeric,ANY
 [(x, i, j, k = NA, l = NA, ..., drop)
 
-# S4 method for antsImage,missing,numeric
+# S4 method for antsImage,missing,numeric,ANY
 [(x, i, j, k = NA, l = NA, ..., drop)
 
-# S4 method for antsImage,numeric,missing
+# S4 method for antsImage,numeric,missing,ANY
 [(x, i, j, k = NA, l = NA, ..., drop)
 
-# S4 method for antsImage,missing,missing
+# S4 method for antsImage,missing,missing,ANY
 [(x, i, j, k = NA, l = NA, ..., drop)</code></pre></div>
     </div>
 
diff --git a/docs/reference/buildTemplate.html b/docs/reference/buildTemplate.html
index d84b1346..1720468d 100644
--- a/docs/reference/buildTemplate.html
+++ b/docs/reference/buildTemplate.html
@@ -157,7 +157,7 @@ <h2>Examples</h2>
 <span class="r-out co"><span class="r-pr">#&gt;</span> ================================================================================</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> Averaging warped composed transforms</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> ================================================================================</span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> Blending template image2.53022264227455</span>
+<span class="r-msg co"><span class="r-pr">#&gt;</span> Blending template image2.59687615269011</span>
 </code></pre></div>
     </div>
   </div>
diff --git a/docs/reference/fitBsplineObjectToScatteredData.html b/docs/reference/fitBsplineObjectToScatteredData.html
index b08e305d..3437c5fc 100644
--- a/docs/reference/fitBsplineObjectToScatteredData.html
+++ b/docs/reference/fitBsplineObjectToScatteredData.html
@@ -222,7 +222,6 @@ <h2>Examples</h2>
 <span class="r-in"><span>  numberOfFittingLevels <span class="op">=</span> <span class="fl">7</span>, meshSize <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1</span>, <span class="fl">1</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">bsplineImage</span><span class="op">)</span></span></span>
-<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>couldn't connect to display "/private/tmp/com.apple.launchd.eGFfXWyHAN/org.xquartz:0"</span>
 <span class="r-plt img"><img src="fitBsplineObjectToScatteredData-2.png" alt="" width="700" height="433"></span>
 <span class="r-in"><span></span></span>
 </code></pre></div>
diff --git a/docs/reference/imagesToMatrix.html b/docs/reference/imagesToMatrix.html
index 98aa581e..82de79ee 100644
--- a/docs/reference/imagesToMatrix.html
+++ b/docs/reference/imagesToMatrix.html
@@ -118,7 +118,7 @@ <h2>Examples</h2>
 <span class="r-in"><span><span class="va">mask</span> <span class="op">&lt;-</span> <span class="fu"><a href="getMask.html">getMask</a></span><span class="op">(</span><span class="fu"><a href="antsImageRead.html">antsImageRead</a></span><span class="op">(</span><span class="va">imageList</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span><span class="op">)</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">mat</span> <span class="op">&lt;-</span> <span class="fu">imagesToMatrix</span><span class="op">(</span><span class="va">imageList</span>, <span class="va">mask</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/dim.html" class="external-link">dim</a></span><span class="op">(</span><span class="va">mat</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1]  3 51</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1]     3 18017</span>
 <span class="r-in"><span></span></span>
 </code></pre></div>
     </div>
diff --git a/docs/reference/index.html b/docs/reference/index.html
index afa14f25..bfd3522d 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -454,6 +454,10 @@ <h2 id="all-functions">All functions <a href="#all-functions" class="anchor" ari
           <p><code><a href="atropos.html">atropos()</a></code> </p>
         </td>
         <td><p>FMM Segmentation</p></td>
+      </tr><tr><td>
+          <p><code><a href="ba_svd.html">ba_svd()</a></code> </p>
+        </td>
+        <td><p>No fail SVD function that switches to rsvd if svd fails</p></td>
       </tr><tr><td>
           <p><code><a href="basicInPaint.html">basicInPaint()</a></code> </p>
         </td>
@@ -488,7 +492,7 @@ <h2 id="all-functions">All functions <a href="#all-functions" class="anchor" ari
         </td>
         <td><p>Boxplot of Values in an Image</p></td>
       </tr><tr><td>
-          <p><code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;logical&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;array&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;matrix&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;list&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;antsImage&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;antsRegion&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;logical&gt;</i>,<i>&lt;antsRegion&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;array&gt;</i>,<i>&lt;antsRegion&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;matrix&gt;</i>,<i>&lt;antsRegion&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;missing&gt;</i>,<i>&lt;array&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;missing&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;array&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;antsImage&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;ANY&gt;</i>,<i>&lt;antsImage&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;logical&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;logical&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;NULL&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;NULL&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;NULL&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;NULL&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;missing&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;missing&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;missing&gt;</i>,<i>&lt;missing&gt;</i>)</a></code> </p>
+          <p><code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;logical&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;array&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;matrix&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;list&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;antsImage&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;antsRegion&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;logical&gt;</i>,<i>&lt;antsRegion&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;array&gt;</i>,<i>&lt;antsRegion&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;matrix&gt;</i>,<i>&lt;antsRegion&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;numeric&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;missing&gt;</i>,<i>&lt;array&gt;</i>)</a></code> <code><a href="brackets.html">`[&lt;-`(<i>&lt;antsImage&gt;</i>,<i>&lt;missing&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;array&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;antsImage&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;ANY&gt;</i>,<i>&lt;antsImage&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;logical&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;logical&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;NULL&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;missing&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;numeric&gt;</i>,<i>&lt;missing&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> <code><a href="brackets.html">`[`(<i>&lt;antsImage&gt;</i>,<i>&lt;missing&gt;</i>,<i>&lt;missing&gt;</i>,<i>&lt;ANY&gt;</i>)</a></code> </p>
         </td>
         <td><p>Extract or Replace Parts of antsImage Object</p></td>
       </tr><tr><td>
@@ -1204,7 +1208,7 @@ <h2 id="all-functions">All functions <a href="#all-functions" class="anchor" ari
       </tr><tr><td>
           <p><code><a href="read_simlr_data_frames.html">read_simlr_data_frames()</a></code> </p>
         </td>
-        <td><p>Read a list of data frames from disk with specific naming convention</p></td>
+        <td><p>Read a list of data frames from disk with SiMLR-specific naming convention</p></td>
       </tr><tr><td>
           <p><code><a href="reflectImage.html">reflectImage()</a></code> </p>
         </td>
@@ -1529,7 +1533,7 @@ <h2 id="all-functions">All functions <a href="#all-functions" class="anchor" ari
       </tr><tr><td>
           <p><code><a href="write_simlr_data_frames.html">write_simlr_data_frames()</a></code> </p>
         </td>
-        <td><p>Write a list of data frames to disk with specific naming convention</p></td>
+        <td><p>Write a list of data frames to disk with SiMLR-specific naming convention</p></td>
       </tr></tbody></table></div>
 
   <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
diff --git a/docs/reference/kmeansSegmentation.html b/docs/reference/kmeansSegmentation.html
index 13dd434e..126bfb62 100644
--- a/docs/reference/kmeansSegmentation.html
+++ b/docs/reference/kmeansSegmentation.html
@@ -139,11 +139,11 @@ <h2>Examples</h2>
 <span class="r-out co"><span class="r-pr">#&gt;</span>     arr2</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> arr1     0     1     2     3</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    0 47118     0     0     0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    1     0  2384     0     0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    2     0     0  7358     0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    3     0     0     0  8676</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>    1     0  2381     3     0</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>    2     0     2  7351     6</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>    3     0     0     3  8672</span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/identical.html" class="external-link">identical</a></span><span class="op">(</span><span class="va">arr1</span>, <span class="va">arr2</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] FALSE</span>
 <span class="r-in"><span><span class="va">seg</span> <span class="op">&lt;-</span> <span class="fu">kmeansSegmentation</span><span class="op">(</span><span class="va">orig</span>, <span class="fl">3</span>, use_random_seed <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">seg2</span> <span class="op">&lt;-</span> <span class="fu">kmeansSegmentation</span><span class="op">(</span><span class="va">orig</span>, <span class="fl">3</span>, use_random_seed <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">arr1</span> <span class="op">&lt;-</span> <span class="fu"><a href="as.array.html">as.array</a></span><span class="op">(</span><span class="va">seg</span><span class="op">$</span><span class="va">segmentation</span><span class="op">)</span></span></span>
diff --git a/docs/reference/labelStats.html b/docs/reference/labelStats.html
index 1393d058..29f17384 100644
--- a/docs/reference/labelStats.html
+++ b/docs/reference/labelStats.html
@@ -101,13 +101,13 @@ <h2>Examples</h2>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   LabelValue        Mean Min Max   Variance Count Volume   Mass        x</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> 4          0   0.1475076   0 163   11.53692  2949  47184      0   0.0000</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> 1          1  73.7428571   0 125 1535.97657   140   2240  10324 131.2857</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2          2 166.1126126 127 191  259.86088   444   7104  73754 125.6937</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3          3 216.2557726 191 253  221.33660   563   9008 121752 124.4618</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 3          2 166.1126126 127 191  259.86088   444   7104  73754 125.6937</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 2          3 216.2557726 191 253  221.33660   563   9008 121752 124.4618</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>          y  z  t</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> 4   0.0000 NA NA</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> 1 128.9714 NA NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2 126.0541 NA NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3 131.7300 NA NA</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 3 126.0541 NA NA</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 2 131.7300 NA NA</span>
 <span class="r-in"><span><span class="fu">testthat</span><span class="fu">::</span><span class="fu"><a href="https://testthat.r-lib.org/reference/expect_error.html" class="external-link">expect_error</a></span><span class="op">(</span><span class="fu">labelStats</span><span class="op">(</span><span class="va">img</span>, <span class="fu"><a href="as.array.html">as.array</a></span><span class="op">(</span><span class="va">segs1</span><span class="op">$</span><span class="va">segmentation</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu">testthat</span><span class="fu">::</span><span class="fu"><a href="https://testthat.r-lib.org/reference/expect_error.html" class="external-link">expect_error</a></span><span class="op">(</span><span class="fu">labelStats</span><span class="op">(</span><span class="va">img</span>, <span class="fu"><a href="as.array.html">as.array</a></span><span class="op">(</span><span class="va">segs1</span><span class="op">$</span><span class="va">segmentation</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">sub_seg</span> <span class="op">&lt;-</span> <span class="va">segs1</span><span class="op">$</span><span class="va">segmentation</span></span></span>
diff --git a/docs/reference/n3BiasFieldCorrection2.html b/docs/reference/n3BiasFieldCorrection2.html
index 479d3a98..2f06bb9f 100644
--- a/docs/reference/n3BiasFieldCorrection2.html
+++ b/docs/reference/n3BiasFieldCorrection2.html
@@ -161,21 +161,21 @@ <h2>Examples</h2>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/rm.html" class="external-link">rm</a></span><span class="op">(</span><span class="va">img</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/gc.html" class="external-link">gc</a></span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>           used  (Mb) gc trigger  (Mb) limit (Mb) max used  (Mb)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3851602 205.7    5680604 303.4         NA  5680604 303.4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6359614  48.6   20507950 156.5     102400 20507923 156.5</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3999970 213.7    6002884 320.6         NA  6002884 320.6</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6668473  50.9   20952692 159.9     102400 20952681 159.9</span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/rm.html" class="external-link">rm</a></span><span class="op">(</span><span class="va">n3img</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/gc.html" class="external-link">gc</a></span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>           used  (Mb) gc trigger  (Mb) limit (Mb) max used  (Mb)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3851311 205.7    5680604 303.4         NA  5680604 303.4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6359159  48.6   20507950 156.5     102400 20507923 156.5</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3999091 213.6    6002884 320.6         NA  6002884 320.6</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6667038  50.9   20952692 159.9     102400 20952681 159.9</span>
 <span class="r-in"><span><span class="va">fname</span> <span class="op">&lt;-</span> <span class="fu"><a href="getANTsRData.html">getANTsRData</a></span><span class="op">(</span><span class="st">"r16"</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">in_img</span> <span class="op">&lt;-</span> <span class="fu"><a href="antsImageRead.html">antsImageRead</a></span><span class="op">(</span><span class="va">fname</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">n3</span> <span class="op">&lt;-</span> <span class="fu">n3BiasFieldCorrection2</span><span class="op">(</span><span class="va">in_img</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/rm.html" class="external-link">rm</a></span><span class="op">(</span><span class="va">n3</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/gc.html" class="external-link">gc</a></span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>           used  (Mb) gc trigger  (Mb) limit (Mb) max used  (Mb)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3851390 205.7    5680604 303.4         NA  5680604 303.4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6359278  48.6   20507950 156.5     102400 20507923 156.5</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3999170 213.6    6002884 320.6         NA  6002884 320.6</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6667157  50.9   20952692 159.9     102400 20952681 159.9</span>
 <span class="r-in"><span><span class="va">mask</span> <span class="op">&lt;-</span> <span class="va">in_img</span> <span class="op">&gt;</span> <span class="fl">0</span></span></span>
 <span class="r-in"><span><span class="va">mask2</span> <span class="op">&lt;-</span> <span class="fu"><a href="antsImageClone.html">antsImageClone</a></span><span class="op">(</span><span class="va">mask</span>, out_pixeltype <span class="op">=</span> <span class="st">"float"</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="co"># fails</span></span></span>
diff --git a/docs/reference/n4BiasFieldCorrection.html b/docs/reference/n4BiasFieldCorrection.html
index 9539dbaa..cff24e7a 100644
--- a/docs/reference/n4BiasFieldCorrection.html
+++ b/docs/reference/n4BiasFieldCorrection.html
@@ -157,21 +157,21 @@ <h2>Examples</h2>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/rm.html" class="external-link">rm</a></span><span class="op">(</span><span class="va">img</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/gc.html" class="external-link">gc</a></span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>           used  (Mb) gc trigger  (Mb) limit (Mb) max used  (Mb)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3851912 205.8    5680604 303.4         NA  5680604 303.4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6360228  48.6   20507950 156.5     102400 20507923 156.5</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3999692 213.7    6002884 320.6         NA  6002884 320.6</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6668107  50.9   20952692 159.9     102400 20952681 159.9</span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/rm.html" class="external-link">rm</a></span><span class="op">(</span><span class="va">n4img</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/gc.html" class="external-link">gc</a></span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>           used  (Mb) gc trigger  (Mb) limit (Mb) max used  (Mb)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3851345 205.7    5680604 303.4         NA  5680604 303.4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6359313  48.6   20507950 156.5     102400 20507923 156.5</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3999125 213.6    6002884 320.6         NA  6002884 320.6</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6667192  50.9   20952692 159.9     102400 20952681 159.9</span>
 <span class="r-in"><span><span class="va">fname</span> <span class="op">&lt;-</span> <span class="fu"><a href="getANTsRData.html">getANTsRData</a></span><span class="op">(</span><span class="st">"r16"</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">in_img</span> <span class="op">&lt;-</span> <span class="fu"><a href="antsImageRead.html">antsImageRead</a></span><span class="op">(</span><span class="va">fname</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">n4</span> <span class="op">&lt;-</span> <span class="fu">n4BiasFieldCorrection</span><span class="op">(</span><span class="va">in_img</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/rm.html" class="external-link">rm</a></span><span class="op">(</span><span class="va">n4</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/gc.html" class="external-link">gc</a></span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>           used  (Mb) gc trigger  (Mb) limit (Mb) max used  (Mb)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3851424 205.7    5680604 303.4         NA  5680604 303.4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6359432  48.6   20507950 156.5     102400 20507923 156.5</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Ncells 3999204 213.6    6002884 320.6         NA  6002884 320.6</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Vcells 6667311  50.9   20952692 159.9     102400 20952681 159.9</span>
 <span class="r-in"><span><span class="va">mask</span> <span class="op">&lt;-</span> <span class="va">in_img</span> <span class="op">&gt;</span> <span class="fl">0</span></span></span>
 <span class="r-in"><span><span class="va">mask2</span> <span class="op">&lt;-</span> <span class="fu"><a href="antsImageClone.html">antsImageClone</a></span><span class="op">(</span><span class="va">mask</span>, out_pixeltype <span class="op">=</span> <span class="st">"float"</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="co"># fails</span></span></span>
diff --git a/docs/reference/plotPrettyGraph.html b/docs/reference/plotPrettyGraph.html
index 90b726c6..9a1bf5e1 100644
--- a/docs/reference/plotPrettyGraph.html
+++ b/docs/reference/plotPrettyGraph.html
@@ -144,7 +144,7 @@ <h2>Examples</h2>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> copyright (c) 2005, Carter T. Butts, University of California-Irvine</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>  For citation information, type citation("sna").</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>  Type help(package="sna") to get started.</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "/tmp//Rtmp5A3DVJ/filec1b543cfb044.png"</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "/tmp//RtmpqqMYeq/file51c51539d2fc.png"</span>
 <span class="r-in"><span></span></span>
 </code></pre></div>
     </div>
diff --git a/docs/reference/read_simlr_data_frames.html b/docs/reference/read_simlr_data_frames.html
index 2cb4d00a..850d2909 100644
--- a/docs/reference/read_simlr_data_frames.html
+++ b/docs/reference/read_simlr_data_frames.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Read a list of data frames from disk with specific naming convention — read_simlr_data_frames • ANTsR</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Read a list of data frames from disk with specific naming convention — read_simlr_data_frames"><meta property="og:description" content="This function reads a list of data frames from disk into a list,
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Read a list of data frames from disk with SiMLR-specific naming convention — read_simlr_data_frames • ANTsR</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Read a list of data frames from disk with SiMLR-specific naming convention — read_simlr_data_frames"><meta property="og:description" content="This function reads a list of data frames from disk into a list,
 assuming the files are named with a common prefix and the names of the data frames.
 It converts the column named `X` to the row names of the read data frame."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
@@ -61,7 +61,7 @@
       </header><div class="row">
   <div class="col-md-9 contents">
     <div class="page-header">
-    <h1>Read a list of data frames from disk with specific naming convention</h1>
+    <h1>Read a list of data frames from disk with SiMLR-specific naming convention</h1>
     
     <div class="hidden name"><code>read_simlr_data_frames.Rd</code></div>
     </div>
@@ -73,7 +73,7 @@ <h1>Read a list of data frames from disk with specific naming convention</h1>
     </div>
 
     <div id="ref-usage">
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">read_simlr_data_frames</span><span class="op">(</span><span class="va">file_prefix</span>, <span class="va">data_names</span><span class="op">)</span></span></code></pre></div>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">read_simlr_data_frames</span><span class="op">(</span><span class="va">file_prefix</span>, <span class="va">data_names</span>, verbose <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
     </div>
 
     <div id="arguments">
@@ -85,6 +85,10 @@ <h2>Arguments</h2>
 <dt>data_names</dt>
 <dd><p>A character vector of names for the data frames.</p></dd>
 
+
+<dt>verbose</dt>
+<dd><p>boolean</p></dd>
+
 </dl></div>
     <div id="value">
     <h2>Value</h2>
diff --git a/docs/reference/simlr.html b/docs/reference/simlr.html
index 2223c687..f2e2edb7 100644
--- a/docs/reference/simlr.html
+++ b/docs/reference/simlr.html
@@ -169,7 +169,7 @@ <h2>Arguments</h2>
 
 
 <dt>constraint</dt>
-<dd><p>one of none, Grassmann or Stiefel</p></dd>
+<dd><p>one of none, Grassmann, GrassmannInv or Stiefel</p></dd>
 
 
 <dt>energyType</dt>
diff --git a/docs/reference/sparseRegression.html b/docs/reference/sparseRegression.html
index 91bbc9c3..2388a4d4 100644
--- a/docs/reference/sparseRegression.html
+++ b/docs/reference/sparseRegression.html
@@ -202,10 +202,6 @@ <h2>Examples</h2>
 <span class="r-in"><span>  <span class="va">input.train</span>, <span class="va">input.test</span>, <span class="va">demog.train</span>,</span></span>
 <span class="r-in"><span>  <span class="va">demog.test</span>, <span class="va">myregression</span><span class="op">$</span><span class="va">eigenanatomyimages</span>, <span class="va">mymask</span>, <span class="st">"outcome"</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
-<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>the standard deviation is zero</span>
-<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>the standard deviation is zero</span>
-<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>the standard deviation is zero</span>
-<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>the standard deviation is zero</span>
 <span class="r-in"><span><span class="co"># plot(result$outcome.comparison$real, result$outcome.comparison$predicted)</span></span></span>
 <span class="r-in"><span></span></span>
 </code></pre></div>
diff --git a/docs/reference/write_simlr_data_frames.html b/docs/reference/write_simlr_data_frames.html
index c490aa1b..0032f3d5 100644
--- a/docs/reference/write_simlr_data_frames.html
+++ b/docs/reference/write_simlr_data_frames.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Write a list of data frames to disk with specific naming convention — write_simlr_data_frames • ANTsR</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Write a list of data frames to disk with specific naming convention — write_simlr_data_frames"><meta property="og:description" content="This function writes each data frame in a list to a separate CSV file on disk,
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Write a list of data frames to disk with SiMLR-specific naming convention — write_simlr_data_frames • ANTsR</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Write a list of data frames to disk with SiMLR-specific naming convention — write_simlr_data_frames"><meta property="og:description" content="This function writes each data frame in a list to a separate CSV file on disk,
 using the names of each data frame to create unique filenames."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
@@ -60,7 +60,7 @@
       </header><div class="row">
   <div class="col-md-9 contents">
     <div class="page-header">
-    <h1>Write a list of data frames to disk with specific naming convention</h1>
+    <h1>Write a list of data frames to disk with SiMLR-specific naming convention</h1>
     
     <div class="hidden name"><code>write_simlr_data_frames.Rd</code></div>
     </div>
diff --git a/docs/sitemap.xml b/docs/sitemap.xml
index 6e5b83a8..4c765010 100644
--- a/docs/sitemap.xml
+++ b/docs/sitemap.xml
@@ -339,6 +339,9 @@
   <url>
     <loc>/reference/atropos.html</loc>
   </url>
+  <url>
+    <loc>/reference/ba_svd.html</loc>
+  </url>
   <url>
     <loc>/reference/basicInPaint.html</loc>
   </url>
diff --git a/vignettes/simlr_interpretation.Rmd b/vignettes/simlr_interpretation.Rmd
index cb8d6380..1e5845e8 100644
--- a/vignettes/simlr_interpretation.Rmd
+++ b/vignettes/simlr_interpretation.Rmd
@@ -71,11 +71,14 @@ Now we apply the SiMLR algorithm to the simulated multi-view data to find a comm
 
 ```{r step2}
 # Applying SiMLR
-constr='Grassmannx1x1'
-constr='Stiefelx1x1'
-constr='orthox0.1x0.1'
-prepro=c("centerAndScale","np")
-result <- simlr(matlist,constraint=constr,scale=prepro, verbose=TRUE)
+prepro=c( "centerAndScale","np")
+constr='Stiefelx100x1'
+constr='orthox100x0.1'
+constr='Grassmannx100x1'
+result <- simlr(matlist,constraint=constr,scale=prepro, 
+#  mixAlg='pca', energyType='cca', # recommended
+  mixAlg='ica', energyType='regression', # recommended
+  iterations=100, verbose=TRUE)
 
 # Projecting data into the reduced space
 p1 <- mat1 %*% (result$v[[1]])
@@ -321,22 +324,22 @@ paster <- function(vec1, vec2) {
 }
 csearch = as.list( c("none", 
   paster( c("Grassmannx","Stiefelx","orthox"), 
-    c("10x10","1x1","0.1x0.1"))))
+    c("10x10","100x1","100x1","1x1"))))
 # the 10x10 are weights on the optimization term of the energy
 simparms = simlr.parameters( 
     nsimlr_options = list( 2 ),
     prescaling_options = list( 
             c( "robust", "centerAndScale",  "np") ),
-    objectiver_options = list("cca"),
-    mixer_options=list("pca"), 
+    objectiver_options = list("regression",'cca'),
+    mixer_options=list("ica",'pca'), 
     sparval_options=list(  c(0.5,0.5,0.5) ),
     expBeta_options = list( c(0.99) ),
     positivities_options = list(
             c("positive","positive","positive")),
     optimus_options=list( 'lineSearch'),
     constraint_options=csearch,
-    search_type="full",
-    num_samples=5
+    search_type="full"
+#    num_samples=5
     )
 ```