diff --git a/R/DPMGibbsN.R b/R/DPMGibbsN.R
index d9073b1..fe6e026 100644
--- a/R/DPMGibbsN.R
+++ b/R/DPMGibbsN.R
@@ -37,7 +37,6 @@
 #'  is \code{TRUE}.
 #'
 #'@return a object of class \code{DPMclust} with the following attributes:
-#'  \itemize{
 #'      \item{\code{mcmc_partitions}:}{ a list of length \code{N}. Each
 #'       element \code{mcmc_partitions[n]} is a vector of length
 #'       \code{n} giving the partition of the \code{n} observations.}
@@ -58,7 +57,6 @@
 #'      \item{\code{nb_mcmcit}:}{ the number of MCMC iterations}
 #'      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"gaussian"}}
 #'      \item{\code{hyperG0}:}{the prior on the cluster location}
-#'  }
 #'
 #'@author Boris Hejblum
 #'
diff --git a/R/DPMGibbsN_SeqPrior.R b/R/DPMGibbsN_SeqPrior.R
index 75eb0ee..880748a 100644
--- a/R/DPMGibbsN_SeqPrior.R
+++ b/R/DPMGibbsN_SeqPrior.R
@@ -37,7 +37,6 @@
 #'Only used if \code{doPlot} is \code{TRUE}.
 #'
 #'@return a object of class \code{DPMclust} with the following attributes:
-#'  \itemize{
 #'      \item{\code{mcmc_partitions}:}{ a list of length \code{N}. Each
 #'       element \code{mcmc_partitions[n]} is a vector of length
 #'       \code{n} giving the partition of the \code{n} observations.}
@@ -57,7 +56,6 @@
 #'      \item{\code{nb_mcmcit}:}{ the number of MCMC iterations}
 #'      \item{\code{clust_distrib}:}{ the parametric distribution of the mixture component - \code{"gaussian"}}
 #'      \item{\code{hyperG0}:}{ the prior on the cluster location}
-#'  }
 #'
 #'@author Boris Hejblum, Chariff Alkhassim
 #'
diff --git a/R/DPMGibbsN_parallel.R b/R/DPMGibbsN_parallel.R
index e9edf3f..c23b896 100644
--- a/R/DPMGibbsN_parallel.R
+++ b/R/DPMGibbsN_parallel.R
@@ -50,7 +50,6 @@
 #'Only used if \code{doPlot} is \code{TRUE}.
 #'
 #'@return a object of class \code{DPMclust} with the following attributes:
-#'  \itemize{
 #'      \item{\code{mcmc_partitions}:}{ a list of length \code{N}. Each
 #'       element \code{mcmc_partitions[n]} is a vector of length
 #'       \code{n} giving the partition of the \code{n} observations.}
@@ -71,7 +70,6 @@
 #'      \item{\code{nb_mcmcit}:}{ the number of MCMC iterations}
 #'      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"gaussian"}}
 #'      \item{\code{hyperG0}:}{the prior on the cluster location}
-#'  }
 #'
 #'@author Boris Hejblum
 #'
diff --git a/R/DPMGibbsSkewN.R b/R/DPMGibbsSkewN.R
index ba4cd4c..27256c0 100644
--- a/R/DPMGibbsSkewN.R
+++ b/R/DPMGibbsSkewN.R
@@ -37,7 +37,6 @@
 #'Only used if \code{doPlot} is \code{TRUE}.
 #'
 #'@return a object of class \code{DPMclust} with the following attributes:
-#'  \itemize{
 #'      \item{\code{mcmc_partitions}:}{a list of length \code{N}. Each
 #'       element \code{mcmc_partitions[n]} is a vector of length
 #'       \code{n} giving the partition of the \code{n} observations.}
@@ -53,7 +52,6 @@
 #'      \item{\code{nb_mcmcit}:}{the number of MCMC iterations}
 #'      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"skewnorm"}}
 #'      \item{\code{hyperG0}:}{the prior on the cluster location}
-#'  }
 #'
 #'@author Boris Hejblum
 #'
diff --git a/R/DPMGibbsSkewN_parallel.R b/R/DPMGibbsSkewN_parallel.R
index bc2c534..8438141 100644
--- a/R/DPMGibbsSkewN_parallel.R
+++ b/R/DPMGibbsSkewN_parallel.R
@@ -53,7 +53,6 @@
 #'Only used if \code{doPlot} is \code{TRUE}.
 #'
 #'@return a object of class \code{DPMclust} with the following attributes:
-#'  \itemize{
 #'      \item{\code{mcmc_partitions}:}{a list of length \code{N}. Each
 #'       element \code{mcmc_partitions[n]} is a vector of length
 #'       \code{n} giving the partition of the \code{n} observations.}
@@ -69,7 +68,6 @@
 #'      \item{\code{nb_mcmcit}:}{the number of MCMC iterations}
 #'      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"skewnorm"}}
 #'      \item{\code{hyperG0}:}{the prior on the cluster location}
-#'  }
 #'
 #'@author Boris Hejblum
 #'
diff --git a/R/DPMGibbsSkewT.R b/R/DPMGibbsSkewT.R
index 85194af..a66b5a1 100644
--- a/R/DPMGibbsSkewT.R
+++ b/R/DPMGibbsSkewT.R
@@ -60,7 +60,6 @@
 #'Only used if \code{doPlot} is \code{TRUE}.
 #'
 #'@return a object of class \code{DPMclust} with the following attributes:
-#'  \itemize{
 #'      \item{\code{mcmc_partitions}: }{ a list of length \code{N}. Each
 #'       element \code{mcmc_partitions[n]} is a vector of length
 #'       \code{n} giving the partition of the \code{n} observations.}
@@ -77,7 +76,6 @@
 #'      \item{\code{nb_mcmcit}: }{the number of MCMC iterations}
 #'      \item{\code{clust_distrib}: }{the parametric distribution of the mixture component - \code{"skewt"}}
 #'      \item{\code{hyperG0}: }{the prior on the cluster location}
-#'  }
 #'
 #'@author Boris Hejblum
 #'
diff --git a/R/DPMGibbsSkewT_SeqPrior.R b/R/DPMGibbsSkewT_SeqPrior.R
index 9d96ac8..c2eb4c4 100644
--- a/R/DPMGibbsSkewT_SeqPrior.R
+++ b/R/DPMGibbsSkewT_SeqPrior.R
@@ -35,7 +35,6 @@
 #'Only used if \code{doPlot} is \code{TRUE}.
 #'
 #'@return a object of class \code{DPMclust} with the following attributes:
-#'  \itemize{
 #'      \item{\code{mcmc_partitions}:}{a list of length \code{N}. Each
 #'       element \code{mcmc_partitions[n]} is a vector of length
 #'       \code{n} giving the partition of the \code{n} observations.}
@@ -52,7 +51,6 @@
 #'      \item{\code{nb_mcmcit}:}{the number of MCMC iterations}
 #'      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"skewt"}}
 #'      \item{\code{hyperG0}:}{the prior on the cluster location}
-#'  }
 #'
 #'@author Boris Hejblum
 #'
diff --git a/R/DPMGibbsSkewT_SeqPrior_parallel.R b/R/DPMGibbsSkewT_SeqPrior_parallel.R
index 6e2d7de..01a5e95 100644
--- a/R/DPMGibbsSkewT_SeqPrior_parallel.R
+++ b/R/DPMGibbsSkewT_SeqPrior_parallel.R
@@ -46,7 +46,6 @@
 #'Only used if \code{doPlot} is \code{TRUE}.
 #'
 #'@return a object of class \code{DPMclust} with the following attributes:
-#'  \itemize{
 #'      \item{\code{mcmc_partitions}:}{a list of length \code{N}. Each
 #'       element \code{mcmc_partitions[n]} is a vector of length
 #'       \code{n} giving the partition of the \code{n} observations.}
@@ -63,7 +62,6 @@
 #'      \item{\code{nb_mcmcit}:}{the number of MCMC iterations}
 #'      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"skewt"}}
 #'      \item{\code{hyperG0}:}{the prior on the cluster location}
-#'  }
 #'
 #'@author Boris Hejblum
 #'
diff --git a/R/DPMGibbsSkewT_parallel.R b/R/DPMGibbsSkewT_parallel.R
index 4a9d202..198a1d9 100644
--- a/R/DPMGibbsSkewT_parallel.R
+++ b/R/DPMGibbsSkewT_parallel.R
@@ -49,7 +49,6 @@
 #'Only used if \code{doPlot} is \code{TRUE}.
 #'
 #'@return a object of class \code{DPMclust} with the following attributes:
-#'  \itemize{
 #'      \item{\code{mcmc_partitions}:}{a list of length \code{N}. Each
 #'       element \code{mcmc_partitions[n]} is a vector of length
 #'       \code{n} giving the partition of the \code{n} observations.}
@@ -66,7 +65,6 @@
 #'      \item{\code{nb_mcmcit}:}{the number of MCMC iterations}
 #'      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"skewt"}}
 #'      \item{\code{hyperG0}:}{the prior on the cluster location}
-#'  }
 #'
 #'@author Boris Hejblum
 #'
diff --git a/R/DPMpost.R b/R/DPMpost.R
index 8fa1583..a577236 100644
--- a/R/DPMpost.R
+++ b/R/DPMpost.R
@@ -57,7 +57,6 @@
 #'Only used if \code{doPlot} is \code{TRUE}.
 #'
 #'@return a object of class \code{DPMclust} with the following attributes:
-#'  \itemize{
 #'      \item{\code{mcmc_partitions}:}{ a list of length \code{N}. Each
 #'       element \code{mcmc_partitions[n]} is a vector of length
 #'       \code{n} giving the partition of the \code{n} observations.}
@@ -74,7 +73,6 @@
 #'      \item{\code{nb_mcmcit}:}{ the number of MCMC iterations}
 #'      \item{\code{clust_distrib}:}{ the parametric distribution of the mixture component}
 #'      \item{\code{hyperG0}:}{ the prior on the cluster location}
-#'  }
 #'
 #'@author Boris Hejblum
 #'
diff --git a/R/RcppExports.R b/R/RcppExports.R
index 851b0d8..f4a1c6e 100644
--- a/R/RcppExports.R
+++ b/R/RcppExports.R
@@ -49,9 +49,8 @@ FmeasureC_no0 <- function(pred, ref) {
 #'@param c a matrix where each column is one MCMC partition
 #'
 #'@return a list with the following elements:
-#'\itemize{
 #'  \item{\code{Fmeas:}}{ TODO}
-#'}
+#'  \item{\code{cost:}}{ TODO}
 #'@export
 #'
 #'@examples
@@ -382,11 +381,9 @@ mmvtpdfC <- function(x, mean, varcovM, df, Log = TRUE) {
 #'@param loglik logical flag or returning the log-likelihood instead of the likelihood.
 #'Default is \code{TRUE}.
 #'@return a list:
-#'\itemize{
 #'\item{\code{"indiv"}:}{ vector of likelihood of length n;}
 #'\item{\code{"clust"}:}{ vector of likelihood of length K;}
 #'\item{\code{"total"}:}{ total (log)-likelihood;}
-#'}
 #'
 #'@author Boris Hejblum
 #'
@@ -447,11 +444,9 @@ mvnpdfC <- function(x, mean, varcovM, Log = TRUE) {
 #'@param loglik logical flag or returning the log-likelihood instead of the likelihood.
 #'Default is \code{TRUE}.
 #'@return a list:
-#'\itemize{
 #'\item{\code{"indiv"}:}{ vector of likelihood of length n;}
 #'\item{\code{"clust"}:}{ vector of likelihood of length K;}
 #'\item{\code{"total"}:}{ total (log)-likelihood;}
-#'}
 #'
 #'@author Boris Hejblum
 #'
@@ -475,11 +470,9 @@ mvsnlikC <- function(x, c, clustval, xi, psi, sigma, loglik = TRUE) {
 #'@param loglik logical flag or returning the log-likelihood instead of the likelihood.
 #'Default is \code{TRUE}.
 #'@return a list:
-#'\itemize{
 #'\item{\code{"indiv"}:}{ vector of likelihood of length n;}
 #'\item{\code{"clust"}:}{ vector of likelihood of length K;}
 #'\item{\code{"total"}:}{ total (log)-likelihood;}
-#'}
 #'
 #'@author Boris Hejblum
 #'
diff --git a/R/cluster_est_Fmeasure.R b/R/cluster_est_Fmeasure.R
index a196886..40c7d5d 100644
--- a/R/cluster_est_Fmeasure.R
+++ b/R/cluster_est_Fmeasure.R
@@ -10,7 +10,6 @@
 #'partition from \code{c} used to break ties when minimizing the cost function
 #'
 #'@return a \code{list}:
-#'  \itemize{
 #'      \item{\code{c_est}:}{ a vector of length \code{n}. Point estimate of the partition}
 #'      \item{\code{cost}:}{ a vector of length \code{N}. \code{cost[j]} is the cost
 #'      associated to partition \code{c[[j]]}}
@@ -18,7 +17,6 @@
 #'      (see \code{\link{similarityMat}})}
 #'      \item{\code{opt_ind}:}{ the index of the optimal partition
 #'      among the MCMC iterations.}
-#'  }
 #'
 #'
 #'@author Francois Caron, Boris Hejblum
diff --git a/R/cluster_est_Mbinder_norm.R b/R/cluster_est_Mbinder_norm.R
index 88eaa76..e19facb 100644
--- a/R/cluster_est_Mbinder_norm.R
+++ b/R/cluster_est_Mbinder_norm.R
@@ -31,7 +31,6 @@
 #'partition from \code{c} used to break ties when minimizing the cost function
 #'
 #'@return a \code{list}:
-#'  \itemize{
 #'      \item{\code{c_est}:}{ a vector of length \code{n}. Point estimate of the partition}
 #'      \item{\code{cost}:}{ a vector of length \code{N}. \code{cost[j]} is the cost
 #'      associated to partition \code{c[[j]]}}
@@ -39,7 +38,6 @@
 #'      (see \code{\link{similarityMat}})}
 #'      \item{\code{opt_ind}:}{ the index of the optimal partition
 #'      among the MCMC iterations.}
-#'  }
 #'
 #'
 #'@author Chariff Alkhassim
diff --git a/R/cluster_est_pear.R b/R/cluster_est_pear.R
index 6796e9e..2d12e45 100644
--- a/R/cluster_est_pear.R
+++ b/R/cluster_est_pear.R
@@ -7,7 +7,6 @@
 #'
 #'
 #'@return a \code{list}:
-#'  \itemize{
 #'      \item{\code{c_est}:}{ a vector of length \code{n}. Point estimate of the partition}
 #'      \item{\code{pear}:}{ a vector of length \code{N}. \code{pear[j]} is the
 #'      posterior expected adjusted Rand index associated to partition \code{c[[j]]}}
@@ -15,7 +14,6 @@
 #'      (see \code{\link{similarityMat}})}
 #'      \item{\code{opt_ind}:}{ the index of the optimal partition
 #'      among the MCMC iterations.}
-#'  }
 #'
 #'
 #'@author Chariff Alkhassim
diff --git a/R/evalClustLoss.R b/R/evalClustLoss.R
index 60342b3..1a3601b 100644
--- a/R/evalClustLoss.R
+++ b/R/evalClustLoss.R
@@ -12,10 +12,10 @@
 #'Either "F-measure" or "Binder" (see Details). Default is "F-measure".
 #'
 #'@param a only relevant if \code{lossFn} is "Binder". Penalty for wrong
-#'co-clustering in \code{c} compared to code{gs}. Defaults is 1.
+#'co-clustering in \code{c} compared to \code{gs}. Defaults is 1.
 #'
 #'@param b only relevant if \code{lossFn} is "Binder". Penalty for missed
-#'co-clustering in \code{c} compared to code{gs}. Defaults is 1.
+#'co-clustering in \code{c} compared to \code{gs}. Defaults is 1.
 #'
 #'@return the cost of the point estimate \code{c} in regard of the
 #'gold standard \code{gs} for a given loss function.
diff --git a/R/postProcess.DPMMclust.R b/R/postProcess.DPMMclust.R
index 9f972b3..b656606 100644
--- a/R/postProcess.DPMMclust.R
+++ b/R/postProcess.DPMMclust.R
@@ -19,14 +19,12 @@
 #'@param ... further arguments passed to or from other methods
 #'
 #'@return a \code{list}:
-#'  \itemize{
 #'      \item{\code{burnin}:}{an integer passing along the \code{burnin} argument}
 #'      \item{\code{thin}:}{an integer passing along the \code{thin} argument}
 #'      \item{\code{lossFn}:}{a character string passing along the \code{lossFn} argument}
 #'      \item{\code{point_estim}:}{}
 #'      \item{\code{loss}:}{}
 #'      \item{\code{index_estim}:}{}
-#'  }
 #'
 #'@details The cost of a point estimate partition is calculated using either a pairwise
 #' coincidence loss function (Binder), or 1-Fmeasure (F-measure).
diff --git a/R/summary.DPMMclust.R b/R/summary.DPMMclust.R
index fef8275..1925aa7 100644
--- a/R/summary.DPMMclust.R
+++ b/R/summary.DPMMclust.R
@@ -21,7 +21,6 @@
 #'@param ... further arguments passed to or from other methods
 #'
 #'@return a \code{list} containing the following elements:
-#'  \itemize{
 #'      \item{\code{nb_mcmcit}:}{ an integer giving the value of \code{m}, the number of retained 
 #'      sampled partitions, i.e. \code{(N - burnin)/thin}}
 #'      \item{\code{burnin}:}{ an integer passing along the \code{burnin} argument}
@@ -45,7 +44,6 @@
 #'      \item{\code{U_SS_list}:}{ a list of length \code{m} containing the containing the lists of sufficient statistics for all the mixture components,
 #'      for each sampled partition}
 #'      \item{\code{data}: a \code{d x n} matrix containing the clustered data}
-#'  }
 #'  
 #'
 #'@details The cost of a point estimate partition is calculated using either a pairwise
diff --git a/cran-comments.md b/cran-comments.md
index 6dfdb0a..2fbcd7e 100644
--- a/cran-comments.md
+++ b/cran-comments.md
@@ -2,7 +2,7 @@
 
 ## Test environments  
  * local R installation, R 4.3.2 on macOS 13.5.2
- * Linux (Ubuntu 20.04), macOS (11.6) and Windows (Server 2019 10.0), R devel and release (through GitHub Actions)
+ * Linux (Ubuntu 22.04), macOS (12.7) and Windows (Server 2022 10.0), R devel and release (through GitHub Actions)
 
 ## R CMD check results  
 0 errors | 0 warnings | 0 note
diff --git a/man/DPMGibbsN.Rd b/man/DPMGibbsN.Rd
index ea70356..4376f15 100644
--- a/man/DPMGibbsN.Rd
+++ b/man/DPMGibbsN.Rd
@@ -57,7 +57,6 @@ is \code{TRUE}.}
 }
 \value{
 a object of class \code{DPMclust} with the following attributes:
- \itemize{
      \item{\code{mcmc_partitions}:}{ a list of length \code{N}. Each
       element \code{mcmc_partitions[n]} is a vector of length
       \code{n} giving the partition of the \code{n} observations.}
@@ -78,7 +77,6 @@ and \code{n} observations in columns.}
      \item{\code{nb_mcmcit}:}{ the number of MCMC iterations}
      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"gaussian"}}
      \item{\code{hyperG0}:}{the prior on the cluster location}
- }
 }
 \description{
 Slice Sampling of the Dirichlet Process Mixture Model with a prior on alpha
diff --git a/man/DPMGibbsN_SeqPrior.Rd b/man/DPMGibbsN_SeqPrior.Rd
index 2aa27c2..30c2b55 100644
--- a/man/DPMGibbsN_SeqPrior.Rd
+++ b/man/DPMGibbsN_SeqPrior.Rd
@@ -57,7 +57,6 @@ Only used if \code{doPlot} is \code{TRUE}.}
 }
 \value{
 a object of class \code{DPMclust} with the following attributes:
- \itemize{
      \item{\code{mcmc_partitions}:}{ a list of length \code{N}. Each
       element \code{mcmc_partitions[n]} is a vector of length
       \code{n} giving the partition of the \code{n} observations.}
@@ -77,7 +76,6 @@ and \code{n} observations in columns.}
      \item{\code{nb_mcmcit}:}{ the number of MCMC iterations}
      \item{\code{clust_distrib}:}{ the parametric distribution of the mixture component - \code{"gaussian"}}
      \item{\code{hyperG0}:}{ the prior on the cluster location}
- }
 }
 \description{
 Slice Sampling of Dirichlet Process Mixture of Gaussian distributions
diff --git a/man/DPMGibbsN_parallel.Rd b/man/DPMGibbsN_parallel.Rd
index ceb528e..e4f8d30 100644
--- a/man/DPMGibbsN_parallel.Rd
+++ b/man/DPMGibbsN_parallel.Rd
@@ -73,7 +73,6 @@ Only used if \code{doPlot} is \code{TRUE}.}
 }
 \value{
 a object of class \code{DPMclust} with the following attributes:
- \itemize{
      \item{\code{mcmc_partitions}:}{ a list of length \code{N}. Each
       element \code{mcmc_partitions[n]} is a vector of length
       \code{n} giving the partition of the \code{n} observations.}
@@ -94,7 +93,6 @@ and \code{n} observations in columns}
      \item{\code{nb_mcmcit}:}{ the number of MCMC iterations}
      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"gaussian"}}
      \item{\code{hyperG0}:}{the prior on the cluster location}
- }
 }
 \description{
 Slice Sampling of the Dirichlet Process Mixture Model
diff --git a/man/DPMGibbsSkewN.Rd b/man/DPMGibbsSkewN.Rd
index 2f1631e..fd3b3ff 100644
--- a/man/DPMGibbsSkewN.Rd
+++ b/man/DPMGibbsSkewN.Rd
@@ -58,7 +58,6 @@ Only used if \code{doPlot} is \code{TRUE}.}
 }
 \value{
 a object of class \code{DPMclust} with the following attributes:
- \itemize{
      \item{\code{mcmc_partitions}:}{a list of length \code{N}. Each
       element \code{mcmc_partitions[n]} is a vector of length
       \code{n} giving the partition of the \code{n} observations.}
@@ -74,7 +73,6 @@ and \code{n} observations in columns}
      \item{\code{nb_mcmcit}:}{the number of MCMC iterations}
      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"skewnorm"}}
      \item{\code{hyperG0}:}{the prior on the cluster location}
- }
 }
 \description{
 Slice Sampling of Dirichlet Process Mixture of skew normal distributions
diff --git a/man/DPMGibbsSkewN_parallel.Rd b/man/DPMGibbsSkewN_parallel.Rd
index 3ee744d..ac9a250 100644
--- a/man/DPMGibbsSkewN_parallel.Rd
+++ b/man/DPMGibbsSkewN_parallel.Rd
@@ -72,7 +72,6 @@ Only used if \code{doPlot} is \code{TRUE}.}
 }
 \value{
 a object of class \code{DPMclust} with the following attributes:
- \itemize{
      \item{\code{mcmc_partitions}:}{a list of length \code{N}. Each
       element \code{mcmc_partitions[n]} is a vector of length
       \code{n} giving the partition of the \code{n} observations.}
@@ -88,7 +87,6 @@ and \code{n} observations in columns}
      \item{\code{nb_mcmcit}:}{the number of MCMC iterations}
      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"skewnorm"}}
      \item{\code{hyperG0}:}{the prior on the cluster location}
- }
 }
 \description{
 If the \code{monitorfile} argument is a character string naming a file to
diff --git a/man/DPMGibbsSkewT.Rd b/man/DPMGibbsSkewT.Rd
index 626c268..dd1b9d9 100644
--- a/man/DPMGibbsSkewT.Rd
+++ b/man/DPMGibbsSkewT.Rd
@@ -81,7 +81,6 @@ Only used if \code{doPlot} is \code{TRUE}.}
 }
 \value{
 a object of class \code{DPMclust} with the following attributes:
- \itemize{
      \item{\code{mcmc_partitions}: }{ a list of length \code{N}. Each
       element \code{mcmc_partitions[n]} is a vector of length
       \code{n} giving the partition of the \code{n} observations.}
@@ -98,7 +97,6 @@ and \code{n} observations in columns}
      \item{\code{nb_mcmcit}: }{the number of MCMC iterations}
      \item{\code{clust_distrib}: }{the parametric distribution of the mixture component - \code{"skewt"}}
      \item{\code{hyperG0}: }{the prior on the cluster location}
- }
 }
 \description{
 Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributions
diff --git a/man/DPMGibbsSkewT_SeqPrior.Rd b/man/DPMGibbsSkewT_SeqPrior.Rd
index 6d5a75d..d4e50a9 100644
--- a/man/DPMGibbsSkewT_SeqPrior.Rd
+++ b/man/DPMGibbsSkewT_SeqPrior.Rd
@@ -56,7 +56,6 @@ Only used if \code{doPlot} is \code{TRUE}.}
 }
 \value{
 a object of class \code{DPMclust} with the following attributes:
- \itemize{
      \item{\code{mcmc_partitions}:}{a list of length \code{N}. Each
       element \code{mcmc_partitions[n]} is a vector of length
       \code{n} giving the partition of the \code{n} observations.}
@@ -73,7 +72,6 @@ and \code{n} observations in columns}
      \item{\code{nb_mcmcit}:}{the number of MCMC iterations}
      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"skewt"}}
      \item{\code{hyperG0}:}{the prior on the cluster location}
- }
 }
 \description{
 Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributions
diff --git a/man/DPMGibbsSkewT_SeqPrior_parallel.Rd b/man/DPMGibbsSkewT_SeqPrior_parallel.Rd
index 8080d75..84963af 100644
--- a/man/DPMGibbsSkewT_SeqPrior_parallel.Rd
+++ b/man/DPMGibbsSkewT_SeqPrior_parallel.Rd
@@ -69,7 +69,6 @@ Only used if \code{doPlot} is \code{TRUE}.}
 }
 \value{
 a object of class \code{DPMclust} with the following attributes:
- \itemize{
      \item{\code{mcmc_partitions}:}{a list of length \code{N}. Each
       element \code{mcmc_partitions[n]} is a vector of length
       \code{n} giving the partition of the \code{n} observations.}
@@ -86,7 +85,6 @@ and \code{n} observations in columns}
      \item{\code{nb_mcmcit}:}{the number of MCMC iterations}
      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"skewt"}}
      \item{\code{hyperG0}:}{the prior on the cluster location}
- }
 }
 \description{
 Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributions
diff --git a/man/DPMGibbsSkewT_parallel.Rd b/man/DPMGibbsSkewT_parallel.Rd
index 861d607..58bc6c8 100644
--- a/man/DPMGibbsSkewT_parallel.Rd
+++ b/man/DPMGibbsSkewT_parallel.Rd
@@ -72,7 +72,6 @@ Only used if \code{doPlot} is \code{TRUE}.}
 }
 \value{
 a object of class \code{DPMclust} with the following attributes:
- \itemize{
      \item{\code{mcmc_partitions}:}{a list of length \code{N}. Each
       element \code{mcmc_partitions[n]} is a vector of length
       \code{n} giving the partition of the \code{n} observations.}
@@ -89,7 +88,6 @@ and \code{n} observations in columns}
      \item{\code{nb_mcmcit}:}{the number of MCMC iterations}
      \item{\code{clust_distrib}:}{the parametric distribution of the mixture component - \code{"skewt"}}
      \item{\code{hyperG0}:}{the prior on the cluster location}
- }
 }
 \description{
 Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributions
diff --git a/man/DPMpost.Rd b/man/DPMpost.Rd
index 0b19986..21abf15 100644
--- a/man/DPMpost.Rd
+++ b/man/DPMpost.Rd
@@ -70,7 +70,6 @@ Only used if \code{doPlot} is \code{TRUE}.}
 }
 \value{
 a object of class \code{DPMclust} with the following attributes:
- \itemize{
      \item{\code{mcmc_partitions}:}{ a list of length \code{N}. Each
       element \code{mcmc_partitions[n]} is a vector of length
       \code{n} giving the partition of the \code{n} observations.}
@@ -87,7 +86,6 @@ and \code{n} observations in columns}
      \item{\code{nb_mcmcit}:}{ the number of MCMC iterations}
      \item{\code{clust_distrib}:}{ the parametric distribution of the mixture component}
      \item{\code{hyperG0}:}{ the prior on the cluster location}
- }
 }
 \description{
 Partially collapse slice Gibbs sampling for Dirichlet process mixture of multivariate
diff --git a/man/Fmeasure_costC.Rd b/man/Fmeasure_costC.Rd
index 068e54c..22d8392 100644
--- a/man/Fmeasure_costC.Rd
+++ b/man/Fmeasure_costC.Rd
@@ -11,9 +11,8 @@ Fmeasure_costC(c)
 }
 \value{
 a list with the following elements:
-\itemize{
  \item{\code{Fmeas:}}{ TODO}
-}
+ \item{\code{cost:}}{ TODO}
 }
 \description{
 C++ implementation of multiple cost computations with the F-measure as the loss
diff --git a/man/cluster_est_Fmeasure.Rd b/man/cluster_est_Fmeasure.Rd
index f5ee34b..f860946 100644
--- a/man/cluster_est_Fmeasure.Rd
+++ b/man/cluster_est_Fmeasure.Rd
@@ -16,7 +16,6 @@ partition from \code{c} used to break ties when minimizing the cost function}
 }
 \value{
 a \code{list}:
- \itemize{
      \item{\code{c_est}:}{ a vector of length \code{n}. Point estimate of the partition}
      \item{\code{cost}:}{ a vector of length \code{N}. \code{cost[j]} is the cost
      associated to partition \code{c[[j]]}}
@@ -24,7 +23,6 @@ a \code{list}:
      (see \code{\link{similarityMat}})}
      \item{\code{opt_ind}:}{ the index of the optimal partition
      among the MCMC iterations.}
- }
 }
 \description{
 Get a point estimate of the partition using the F-measure as the cost function.
diff --git a/man/cluster_est_Mbinder_norm.Rd b/man/cluster_est_Mbinder_norm.Rd
index 552c45d..f15a321 100644
--- a/man/cluster_est_Mbinder_norm.Rd
+++ b/man/cluster_est_Mbinder_norm.Rd
@@ -30,7 +30,6 @@ partition from \code{c} used to break ties when minimizing the cost function}
 }
 \value{
 a \code{list}:
- \itemize{
      \item{\code{c_est}:}{ a vector of length \code{n}. Point estimate of the partition}
      \item{\code{cost}:}{ a vector of length \code{N}. \code{cost[j]} is the cost
      associated to partition \code{c[[j]]}}
@@ -38,7 +37,6 @@ a \code{list}:
      (see \code{\link{similarityMat}})}
      \item{\code{opt_ind}:}{ the index of the optimal partition
      among the MCMC iterations.}
- }
 }
 \description{
 Get a point estimate of the partition using a modified Binder loss function
diff --git a/man/cluster_est_pear.Rd b/man/cluster_est_pear.Rd
index b8220cf..1ebb3bc 100644
--- a/man/cluster_est_pear.Rd
+++ b/man/cluster_est_pear.Rd
@@ -14,7 +14,6 @@ the cluster allocation of observation \code{i=1...n} at iteration
 }
 \value{
 a \code{list}:
- \itemize{
      \item{\code{c_est}:}{ a vector of length \code{n}. Point estimate of the partition}
      \item{\code{pear}:}{ a vector of length \code{N}. \code{pear[j]} is the
      posterior expected adjusted Rand index associated to partition \code{c[[j]]}}
@@ -22,7 +21,6 @@ a \code{list}:
      (see \code{\link{similarityMat}})}
      \item{\code{opt_ind}:}{ the index of the optimal partition
      among the MCMC iterations.}
- }
 }
 \description{
 Gets a point estimate of the partition using posterior expected adjusted
diff --git a/man/evalClustLoss.Rd b/man/evalClustLoss.Rd
index 91ee94c..40cfc16 100644
--- a/man/evalClustLoss.Rd
+++ b/man/evalClustLoss.Rd
@@ -17,10 +17,10 @@ partition of the  \code{n} observations.}
 Either "F-measure" or "Binder" (see Details). Default is "F-measure".}
 
 \item{a}{only relevant if \code{lossFn} is "Binder". Penalty for wrong
-co-clustering in \code{c} compared to code{gs}. Defaults is 1.}
+co-clustering in \code{c} compared to \code{gs}. Defaults is 1.}
 
 \item{b}{only relevant if \code{lossFn} is "Binder". Penalty for missed
-co-clustering in \code{c} compared to code{gs}. Defaults is 1.}
+co-clustering in \code{c} compared to \code{gs}. Defaults is 1.}
 }
 \value{
 the cost of the point estimate \code{c} in regard of the
diff --git a/man/mvnlikC.Rd b/man/mvnlikC.Rd
index aced241..1348847 100644
--- a/man/mvnlikC.Rd
+++ b/man/mvnlikC.Rd
@@ -26,12 +26,10 @@ Default is \code{TRUE}.}
 }
 \value{
 a list:
-\itemize{
 \item{\code{"indiv"}:}{ vector of likelihood of length n;}
 \item{\code{"clust"}:}{ vector of likelihood of length K;}
 \item{\code{"total"}:}{ total (log)-likelihood;}
 }
-}
 \description{
 C++ implementation of multivariate Normal probability density function for multiple inputs
 }
diff --git a/man/mvsnlikC.Rd b/man/mvsnlikC.Rd
index 7d3ea62..226fb4f 100644
--- a/man/mvsnlikC.Rd
+++ b/man/mvsnlikC.Rd
@@ -28,12 +28,10 @@ Default is \code{TRUE}.}
 }
 \value{
 a list:
-\itemize{
 \item{\code{"indiv"}:}{ vector of likelihood of length n;}
 \item{\code{"clust"}:}{ vector of likelihood of length K;}
 \item{\code{"total"}:}{ total (log)-likelihood;}
 }
-}
 \description{
 C++ implementation of multivariate skew normal likelihood function for multiple inputs
 }
diff --git a/man/mvstlikC.Rd b/man/mvstlikC.Rd
index 899ed31..449d9ca 100644
--- a/man/mvstlikC.Rd
+++ b/man/mvstlikC.Rd
@@ -30,12 +30,10 @@ Default is \code{TRUE}.}
 }
 \value{
 a list:
-\itemize{
 \item{\code{"indiv"}:}{ vector of likelihood of length n;}
 \item{\code{"clust"}:}{ vector of likelihood of length K;}
 \item{\code{"total"}:}{ total (log)-likelihood;}
 }
-}
 \description{
 C++ implementation of multivariate skew t likelihood function for multiple inputs
 }
diff --git a/man/postProcess.DPMMclust.Rd b/man/postProcess.DPMMclust.Rd
index 215e9ec..1e9e2e1 100644
--- a/man/postProcess.DPMMclust.Rd
+++ b/man/postProcess.DPMMclust.Rd
@@ -35,14 +35,12 @@ Either "F-measure" or "Binder" (see Details). Default is "F-measure".}
 }
 \value{
 a \code{list}:
- \itemize{
      \item{\code{burnin}:}{an integer passing along the \code{burnin} argument}
      \item{\code{thin}:}{an integer passing along the \code{thin} argument}
      \item{\code{lossFn}:}{a character string passing along the \code{lossFn} argument}
      \item{\code{point_estim}:}{}
      \item{\code{loss}:}{}
      \item{\code{index_estim}:}{}
- }
 }
 \description{
 Post-processing Dirichlet Process Mixture Models results to get
diff --git a/man/summary.DPMMclust.Rd b/man/summary.DPMMclust.Rd
index 0c24ee0..c4ce0b6 100644
--- a/man/summary.DPMMclust.Rd
+++ b/man/summary.DPMMclust.Rd
@@ -35,7 +35,6 @@ computed. Default is \code{FALSE}}
 }
 \value{
 a \code{list} containing the following elements:
- \itemize{
      \item{\code{nb_mcmcit}:}{ an integer giving the value of \code{m}, the number of retained 
      sampled partitions, i.e. \code{(N - burnin)/thin}}
      \item{\code{burnin}:}{ an integer passing along the \code{burnin} argument}
@@ -59,7 +58,6 @@ a \code{list} containing the following elements:
      \item{\code{U_SS_list}:}{ a list of length \code{m} containing the containing the lists of sufficient statistics for all the mixture components,
      for each sampled partition}
      \item{\code{data}: a \code{d x n} matrix containing the clustered data}
- }
 }
 \description{
 Summary methods for \code{DPMMclust} objects.
diff --git a/src/FmeasureC.cpp b/src/FmeasureC.cpp
index c2f268f..888cea9 100644
--- a/src/FmeasureC.cpp
+++ b/src/FmeasureC.cpp
@@ -143,9 +143,8 @@ double FmeasureC_no0(const NumericVector & pred, const NumericVector & ref){
 //'@param c a matrix where each column is one MCMC partition
 //'
 //'@return a list with the following elements:
-//'\itemize{
 //'  \item{\code{Fmeas:}}{ TODO}
-//'}
+//'  \item{\code{cost:}}{ TODO}
 //'@export
 //'
 //'@examples
diff --git a/src/mvnlikC.cpp b/src/mvnlikC.cpp
index a89a761..5f0fc65 100644
--- a/src/mvnlikC.cpp
+++ b/src/mvnlikC.cpp
@@ -19,11 +19,9 @@ const double log2pi2 = log(2.0 * M_PI)/2.0;
 //'@param loglik logical flag or returning the log-likelihood instead of the likelihood.
 //'Default is \code{TRUE}.
 //'@return a list:
-//'\itemize{
 //'\item{\code{"indiv"}:}{ vector of likelihood of length n;}
 //'\item{\code{"clust"}:}{ vector of likelihood of length K;}
 //'\item{\code{"total"}:}{ total (log)-likelihood;}
-//'}
 //'
 //'@author Boris Hejblum
 //'
diff --git a/src/mvsnlikC.cpp b/src/mvsnlikC.cpp
index 06d3aff..582aeff 100644
--- a/src/mvsnlikC.cpp
+++ b/src/mvsnlikC.cpp
@@ -20,11 +20,9 @@ const double log2pi2 = log(2.0 * M_PI)/2.0;
 //'@param loglik logical flag or returning the log-likelihood instead of the likelihood.
 //'Default is \code{TRUE}.
 //'@return a list:
-//'\itemize{
 //'\item{\code{"indiv"}:}{ vector of likelihood of length n;}
 //'\item{\code{"clust"}:}{ vector of likelihood of length K;}
 //'\item{\code{"total"}:}{ total (log)-likelihood;}
-//'}
 //'
 //'@author Boris Hejblum
 //'
diff --git a/src/mvstlikC.cpp b/src/mvstlikC.cpp
index c6e459c..8cf9e7d 100644
--- a/src/mvstlikC.cpp
+++ b/src/mvstlikC.cpp
@@ -20,11 +20,9 @@ using namespace arma;
 //'@param loglik logical flag or returning the log-likelihood instead of the likelihood.
 //'Default is \code{TRUE}.
 //'@return a list:
-//'\itemize{
 //'\item{\code{"indiv"}:}{ vector of likelihood of length n;}
 //'\item{\code{"clust"}:}{ vector of likelihood of length K;}
 //'\item{\code{"total"}:}{ total (log)-likelihood;}
-//'}
 //'
 //'@author Boris Hejblum
 //'