diff --git a/CRAN-SUBMISSION b/CRAN-SUBMISSION
index ba8118b..5739bc6 100644
--- a/CRAN-SUBMISSION
+++ b/CRAN-SUBMISSION
@@ -1,3 +1,3 @@
-Version: 1.2.0
-Date: 2023-09-11 22:08:20 UTC
-SHA: ba10aa7dd9c9ea57675350652ba4e2bf4df1b7cf
+Version: 1.3.1
+Date: 2024-01-24 17:50:23 UTC
+SHA: 762aac6f412d4cd1d25d68b5d75be87a00614097
diff --git a/DESCRIPTION b/DESCRIPTION
index 9bba153..a4ab7f1 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -44,7 +44,6 @@ BugReports: https://github.com/noaa-nwfsc/zoid/issues
 Depends: 
     R (>= 3.4.0)
 Imports: 
-    compositions,
     gtools,
     methods,
     Rcpp (>= 0.12.0),
diff --git a/NEWS.md b/NEWS.md
index c9e7a6a..7268fd1 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,11 @@
+# zoid 1.3.1
+
+* Remove dependency on compositions package, change URLs to noaa-nwfsc
+
+# zoid 1.3.0
+
+* Updated models to allow for random effects
+
 # zoid 1.2.0
 
 * Updated Stan code to reflect changes needed to be compatible with Stan 2.26 (arrays)
diff --git a/R/fitting.R b/R/fitting.R
index 2d875fd..0f787af 100644
--- a/R/fitting.R
+++ b/R/fitting.R
@@ -30,18 +30,18 @@
 #'   nrow = 3, byrow = TRUE
 #' )
 #' # fit a model with no covariates
-#' fit <- fit_zoid(data_matrix = y)
+#' fit <- fit_zoid(data_matrix = y, chains = 1, iter = 100)
 #'
 #' # fit a model with 1 factor
 #' design <- data.frame("fac" = c("spring", "spring", "fall"))
-#' fit <- fit_zoid(formula = ~fac, design_matrix = design, data_matrix = y)
+#' fit <- fit_zoid(formula = ~fac, design_matrix = design, data_matrix = y, chains = 1, iter = 100)
 #' }
 #' # try a model with random effects
 #' set.seed(123)
 #' y <- matrix(runif(99,1,4), ncol=3)
 #' design <- data.frame("fac" = sample(letters[1:5], size=nrow(y), replace=TRUE))
 #' design$fac <- as.factor(design$fac)
-#' fit <- fit_zoid(formula = ~(1|fac), design_matrix = design, data_matrix = y)
+#' fit <- fit_zoid(formula = ~(1|fac), design_matrix = design, data_matrix = y, chains = 1, iter = 100)
 #'
 fit_zoid <- function(formula = NULL,
                          design_matrix,
diff --git a/inst/CITATION b/inst/CITATION
index 2276d8b..2cd721c 100644
--- a/inst/CITATION
+++ b/inst/CITATION
@@ -14,5 +14,5 @@ bibentry(bibtype = "Manual",
                     ),
          year = year,
          note = note,
-         url = "https://nwfsc-cb.github.io/zoid/")
+         url = "https://noaa-nwfsc.github.io/zoid/")
 
diff --git a/man/fit_dirichlet.Rd b/man/fit_dirichlet.Rd
new file mode 100644
index 0000000..ea2bba7
--- /dev/null
+++ b/man/fit_dirichlet.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/fit_prior.R
+\name{fit_dirichlet}
+\alias{fit_dirichlet}
+\title{Extract point estimates of compositions from fitted model.}
+\usage{
+fit_dirichlet(data)
+}
+\arguments{
+\item{data}{The data to fit the dirichlet distribution to}
+}
+\description{
+Extract point estimates of compositions from fitted model.
+}
diff --git a/man/fit_zoid.Rd b/man/fit_zoid.Rd
index 12ba33e..c7ce016 100644
--- a/man/fit_zoid.Rd
+++ b/man/fit_zoid.Rd
@@ -57,17 +57,17 @@ y <- matrix(c(3.77, 6.63, 2.60, 0.9, 1.44, 0.66, 2.10, 3.57, 1.33),
   nrow = 3, byrow = TRUE
 )
 # fit a model with no covariates
-fit <- fit_zoid(data_matrix = y)
+fit <- fit_zoid(data_matrix = y, chains = 1, iter = 100)
 
 # fit a model with 1 factor
 design <- data.frame("fac" = c("spring", "spring", "fall"))
-fit <- fit_zoid(formula = ~fac, design_matrix = design, data_matrix = y)
+fit <- fit_zoid(formula = ~fac, design_matrix = design, data_matrix = y, chains = 1, iter = 100)
 }
 # try a model with random effects
 set.seed(123)
 y <- matrix(runif(99,1,4), ncol=3)
 design <- data.frame("fac" = sample(letters[1:5], size=nrow(y), replace=TRUE))
 design$fac <- as.factor(design$fac)
-fit <- fit_zoid(formula = ~(1|fac), design_matrix = design, data_matrix = y)
+fit <- fit_zoid(formula = ~(1|fac), design_matrix = design, data_matrix = y, chains = 1, iter = 100)
 
 }