diff --git a/R/fit_nhmm.R b/R/fit_nhmm.R
index 4225d34..3c78411 100644
--- a/R/fit_nhmm.R
+++ b/R/fit_nhmm.R
@@ -243,7 +243,7 @@ fit_nhmm <- function(model, inits, init_sd, restarts, lambda, method,
       
       logliks <- unlist(lapply(out, "[[", "penalized_logLik")) * n_obs
       optimum <- out[[which.max(logliks)]]
-      init <- setNames(
+      init <- stats::setNames(
         optimum[c("eta_pi", "eta_A", "eta_B")], c("pi", "A", "B")
       )
       if (save_all_solutions) {
diff --git a/man/estimate_mnhmm.Rd b/man/estimate_mnhmm.Rd
index a64e5f7..de477dd 100644
--- a/man/estimate_mnhmm.Rd
+++ b/man/estimate_mnhmm.Rd
@@ -21,6 +21,8 @@ estimate_mnhmm(
   inits = "random",
   init_sd = 2,
   restarts = 0L,
+  lambda = 0,
+  method = "EM",
   store_data = TRUE,
   ...
 )
@@ -82,6 +84,14 @@ of the regression coefficients to zero, use \code{init_sd = 0}.}
 \item{restarts}{Number of times to run optimization using random starting
 values (in addition to the final run). Default is 0.}
 
+\item{lambda}{Penalization factor \code{lambda} for penalized log-likelihood, where the
+penalization is \code{lambda * sum(parameters^2)/(2 * n_obs)}, where \code{n_obs} is
+the number of non-missing observations.}
+
+\item{method}{Optimization method used. Default is \code{"EM"} which uses EM
+algorithm with L-BFGS in the M-step. Another option is \code{"DNM"} which uses
+direct maximization of the log-likelihood using \code{\link[nloptr:nloptr]{nloptr::nloptr()}}.}
+
 \item{store_data}{If \code{TRUE} (default), original data frame passed as \code{data}
 is stored to the model object. For large datasets, this can be set to
 \code{FALSE}, in which case you might need to pass the data separately to some
diff --git a/man/estimate_nhmm.Rd b/man/estimate_nhmm.Rd
index ab2d245..eb9d3d5 100644
--- a/man/estimate_nhmm.Rd
+++ b/man/estimate_nhmm.Rd
@@ -18,7 +18,7 @@ estimate_nhmm(
   inits = "random",
   init_sd = 2,
   restarts = 0L,
-  penalty = 0,
+  lambda = 0,
   method = "EM",
   store_data = TRUE,
   ...
@@ -71,8 +71,8 @@ of the regression coefficients to zero, use \code{init_sd = 0}.}
 \item{restarts}{Number of times to run optimization using random starting
 values (in addition to the final run). Default is 0.}
 
-\item{penalty}{Penalization factor for penalized log-likelihood, where the
-penalization is \code{penalty * sum(parameters^2)/(2 * n_obs)}, where \code{n_obs} is
+\item{lambda}{Penalization factor \code{lambda} for penalized log-likelihood, where the
+penalization is \code{lambda * sum(parameters^2)/(2 * n_obs)}, where \code{n_obs} is
 the number of non-missing observations.}
 
 \item{method}{Optimization method used. Default is \code{"EM"} which uses EM
diff --git a/tests/testthat/test-build_hmm.R b/tests/testthat/test-build_hmm.R
index 3c4dc7d..54ba72c 100644
--- a/tests/testthat/test-build_hmm.R
+++ b/tests/testthat/test-build_hmm.R
@@ -83,11 +83,11 @@ test_that("build_hmm returns the correct probabilities", {
   
   expect_equal(
     rowSums(model$transition_probs),
-    setNames(rep(1, s), paste("State", 1:s))
+    stats::setNames(rep(1, s), paste("State", 1:s))
   )
   expect_equal(
     rowSums(model$emission_probs),
-    setNames(rep(1, s), paste("State", 1:s))
+    stats::setNames(rep(1, s), paste("State", 1:s))
   )
   expect_equal(colnames(model$emission_probs), letters[1:s])
   expect_true(all(model$transition_probs >= 0))
diff --git a/tests/testthat/test-build_mm.R b/tests/testthat/test-build_mm.R
index b5a2a37..09300d1 100644
--- a/tests/testthat/test-build_mm.R
+++ b/tests/testthat/test-build_mm.R
@@ -86,11 +86,11 @@ test_that("build_mm returns the correct probabilities", {
   )
   expect_equal(
     rowSums(model$transition_probs),
-    setNames(rep(1, s), letters[1:s])
+    stats::setNames(rep(1, s), letters[1:s])
   )
   expect_equal(
     rowSums(model$emission_probs),
-    setNames(rep(1, s), letters[1:s])
+    stats::setNames(rep(1, s), letters[1:s])
   )
   expect_true(all(model$transition_probs >= 0))
   expect_true(all(model$emission_probs >= 0))
diff --git a/tests/testthat/test-build_mmm.R b/tests/testthat/test-build_mmm.R
index dbbfa3b..356c475 100644
--- a/tests/testthat/test-build_mmm.R
+++ b/tests/testthat/test-build_mmm.R
@@ -68,6 +68,6 @@ test_that("build_mmm returns the correct number of states", {
   )
   expect_equal(
     lengths(model$initial_probs),
-    setNames(rep(s, k), paste("Cluster", 1:k))
+    stats::setNames(rep(s, k), paste("Cluster", 1:k))
   )
 })