fixed bad markup

R/summary.DPMMclust.R

@@ -21,29 +21,29 @@
 #'@param ... further arguments passed to or from other methods
 #'
 #'@return a \code{list} containing the following elements:
-#'      \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}
-#'      \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{clust_distrib}:}{ a character string passing along the \code{clust_distrib} argument }
-#'      \item{\code{point_estim}:}{ a \code{list} containing: \itemize{
-#'          \item{\code{c_est}:}{ a vector of length \code{n}containing the point estimated clustering for each observations}
-#'          \item{\code{cost}:}{ a vector of length \code{m} containing the cost of each sampled partition}
-#'          \item{\code{Fmeas}:}{ if \code{lossFn} is \code{'F-measure'}, the \code{m x m} matrix of total F-measures for each pair of sampled partitions}
-#'          \item{\code{opt_ind}:}{ the index of the point estimate partition among the \code{m} sampled}
-#'      }}
-#'      \item{\code{loss}:}{ the loss for the point estimate. \code{NA} if \code{lossFn} is not \code{'Binder'}}
-#'      \item{\code{param_posterior}:}{ a list containing the parametric approximation of the posterior,
-#'      suitable to be plugged in as prior for a new MCMC algorithm run}
-#'      \item{\code{mcmc_partitions}:}{ a list containing the \code{m} sampled partitions}
-#'      \item{\code{alpha}:}{ a vector of length \code{m} with the values of the \code{alpha} DP parameter}
-#'      \item{\code{index_estim}:}{ the index of the point estimate partition among the \code{m} sampled}
-#'      \item{\code{hyperG0}:}{ a list passing along the prior, i.e. the \code{hyperG0} argument}
-#'      \item{\code{logposterior_list}:}{ a list of length \code{m} containing the logposterior and its decomposition, for each sampled partition}
-#'      \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}
+#'\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}
+#'\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{clust_distrib}:}{ a character string passing along the \code{clust_distrib} argument }
+#'\item{\code{point_estim}:}{ a \code{list} containing: \itemize{
+#'    \item{\code{c_est}:}{ a vector of length \code{n}containing the point estimated clustering for each observations}
+#'    \item{\code{cost}:}{ a vector of length \code{m} containing the cost of each sampled partition}
+#'    \item{\code{Fmeas}:}{ if \code{lossFn} is \code{'F-measure'}, the \code{m x m} matrix of total F-measures for each pair of sampled partitions}
+#'    \item{\code{opt_ind}:}{ the index of the point estimate partition among the \code{m} sampled}
+#'}}
+#'\item{\code{loss}:}{ the loss for the point estimate. \code{NA} if \code{lossFn} is not \code{'Binder'}}
+#'\item{\code{param_posterior}:}{ a list containing the parametric approximation of the posterior,
+#'suitable to be plugged in as prior for a new MCMC algorithm run}
+#'\item{\code{mcmc_partitions}:}{ a list containing the \code{m} sampled partitions}
+#'\item{\code{alpha}:}{ a vector of length \code{m} with the values of the \code{alpha} DP parameter}
+#'\item{\code{index_estim}:}{ the index of the point estimate partition among the \code{m} sampled}
+#'\item{\code{hyperG0}:}{ a list passing along the prior, i.e. the \code{hyperG0} argument}
+#'\item{\code{logposterior_list}:}{ a list of length \code{m} containing the logposterior and its decomposition, for each sampled partition}
+#'\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