Added value for documentation of several functions

R/alignPosterior.R

@@ -4,6 +4,8 @@
 #'
 #' @param hM a fitted \code{Hmsc} model object
 #'
+#' @return an \code{Hmsc} model object that is identical to the input except the posterior being aligned
+#'
 #' @examples
 #' # Align the posterior for a previously fitted HMSC model
 #' m = alignPosterior(TD$m)

R/computeDataParameters.R

@@ -4,6 +4,8 @@
 #'
 #' @param hM a fitted \code{Hmsc} model object
 #'
+#' @return a list including pre-computed matrix inverses and determinants (for phylogenetic and spatial random effects) needed in MCMC sampling
+#'
 #' @importFrom stats dist
 #' @importFrom FNN get.knn
 #' @importFrom Matrix .sparseDiagonal t solve

R/computeInitialParameters.R

@@ -5,6 +5,8 @@
 #' @param hM a fitted \code{Hmsc} model object
 #' @param initPar initial parameter values
 #'
+#' @return a list of Hmsc model parameters
+#'
 #' @importFrom stats glm.fit lm.fit coef rgamma rnorm binomial poisson
 #'    cov runif
 #' @importFrom abind abind

R/computePredictedValues.R

@@ -16,6 +16,8 @@
 #' @param updater a named list, specifying which conditional updaters should be ommitted
 #' @param verbose the interval between MCMC steps printed to the console
 #'
+#' @return an array of model predictions, made for each posterior sample
+#'
 #' @details If the option \code{partition} is not used, the posterior predictive distribution is based on the model
 #' fitted to the full data. If the option \code{partition} is used but \code{partition.sp} is not used, the posterior predictive distribution
 #' is based on cross-validation over the sampling units. If \code{partition.sp} is additionally used, then, when predictions are made for

R/constructGradient.R

@@ -7,7 +7,7 @@
 #' @param non.focalVariables list giving assumptions on how non-focal variables co-vary with the focal variable
 #' @param ngrid number of points along the gradient (for continuous focal variables)
 #'
-#'#' @return a named list with slots \code{XDataNew}, \code{studyDesignNew} and \code{rLNew}
+#' @return a named list with slots \code{XDataNew}, \code{studyDesignNew} and \code{rLNew}
 #'
 #' @details
 #' \code{non.focalVariables} is a list, of which each element is on the form variable=list(type,value),

R/createPartition.R

@@ -6,6 +6,8 @@
 #' @param nfolds number of cross-validation folds
 #' @param column name or index of the column in the \code{studyDesign} matrix, corresponding to the level for which units are splitted into folds
 #'
+#' @return a vector describing the fold of each sampling unit
+#'
 #' @examples
 #' # Create 3 folds for a HMSC object
 #' partition = createPartition(TD$m, nfolds = 3)

R/samplePrior.R

@@ -5,9 +5,10 @@
 #' @param hM a fitted \code{Hmsc} model object
 #' @param dataParList list of data parameters (see \code{\link{computeDataParameters}})
 #'
+#' @return A named list containing the Hmsc model parameters
+#'
 #' @importFrom stats rgamma rnorm
 #' @importFrom mvtnorm rmvnorm
-## is the next a typo of the previous?
 #' @importFrom MASS mvrnorm
 #' @importFrom MCMCpack riwish