Minor (typo) fixes in documentation

pkg/DESCRIPTION

@@ -8,7 +8,7 @@ LazyLoad: yes
 Authors@R: c( person("Patrick","Bogaart",role="aut",email="pwbogaart@gmail.com"), person("Mark", "van der Loo", role=c("aut","cre"),email="mark.vanderloo@gmail.com"), person("Jeroen", "Pannekoek", role="aut"))
 Description: The TRIM model is widely used for estimating growth and decline of animal populations
     based on (possibly sparsly available) count data. The current package is a reimplementation of the 
-    original TRIM software of J. Pannekoek.
+    original TRIM software developed at Statistics Netherlands by Jeroen Pannekoek.
 Version: 1.0.0
 Imports: methods, utils, stats, graphics, grDevices
 URL: https://github.com/markvanderloo/rtrim

pkg/R/rtrim-pkg.R

@@ -1,18 +1,19 @@
 #' Trend and Indices for Monitoring Data
 #'
-#' The TRIIM model is used to estimate species populations based on frequent 
-#' (annual) counts at a varying collection of sites. The model is able to take 
+#' The TRIM model is used to estimate species populations based on frequent
+#' (annual) counts at a varying collection of sites. The model is able to take
 #' account of missing data by imputing prior to estimation of population totals.
 #' The current package is a complete re-implementation of the \code{Delphi}
-#' based 
+#' based
 #' \href{https://www.cbs.nl/en-gb/society/nature-and-environment/indices-and-trends--trim--}{TRIM}
-#' software by J. Pannekoek.
+#' software developed at Statistics Netherlands by Jeroen Pannekoek.
 #'
 #'
 #' @section Getting started:
 #'
-#' Users of the original TRIM software can get started by following the \href{../doc/rtrim_for_TRIM_users.html}{rtrim for trim users} manual.
-#'
+#' Users of the original TRIM software can get started by following the
+#' \href{../doc/rtrim_for_TRIM_users.html}{rtrim for trim users} or
+#' following the \href{../doc/Skylark_example.html}{TRIM by example} manuals.
 #'
 #' @name rtrim-package
 #' @docType package

pkg/R/trim_index.R

@@ -61,13 +61,16 @@
 #' @param which Selector to distinguish between time indices based on the imputed data (default),
 #' the fitted model, or both.
 #' @param covars Switch to compute indices for covariate categories as well.
-#' @param base Base time point, for which the index is 1
+#' @param base Base time point, for which the index is 1. If the data contains J time points,
+#' the base time point can be given in the interval 1...J, or,
+#' if the time points are proper years, say year1...yearn, the base year can be given.
+#' So, if the data range 2000...2016, \code{base=2} and \code{base=2001} are equivalent.
 #'
-#' @return a data frame containing indices and their uncertainty expressed as
+#' @return A data frame containing indices and their uncertainty expressed as
 #'   standard error. Depending on the chosen output, columns \code{fitted}
 #'   and \code{se_fit}, and/or \code{imputed} and \code{se_imp} are present.
-#'   If \code{covars} is \code{TRUE}, indices are not only computed both for the overall data set,
-#'   and the individual covariate categories. In this case additional columns
+#'   If \code{covars} is \code{TRUE}, additional indices are computed for the
+#'   individual covariate categories. In this case additional columns
 #'   \code{covariate} and \code{category} are present. The overall indices are
 #'   marked as covariate `Overall' and category 0.
 #'

pkg/R/trim_post.R

@@ -43,7 +43,7 @@ print.trim <- function(x,...){
 #'
 #' data(skylark)
 #' z <- trim(count ~ time + site,data=skylark,model=2,overdisp=TRUE)
-#' 
+#'
 #' summary(z)
 summary.trim <- function(object,...) {
 
@@ -222,7 +222,7 @@ coef.trim <- function(object,
 #' @param x TRIM output structure (i.e., output of a call to \code{trim})
 #' @param which select what totals to compute (see \code{Details} section).
 #'
-#' @return a \code{data.frame} with subclass \code{trim.totals}
+#' @return A \code{data.frame} with subclass \code{trim.totals}
 #'  (for pretty-printing). The columns are \code{time}, \code{fitted}
 #'  and \code{se_fit} (for standard error), and/or \code{imputed}
 #'  and \code{se_imp}, depending on the selection.
@@ -239,9 +239,6 @@ coef.trim <- function(object,
 #' values predicted by the model.}
 #' }
 #'
-#'
-#' @return A \code{data.frame} with time totals and their standard errors.
-#'
 #' @export
 #'
 #' @family analyses
@@ -328,7 +325,7 @@ vcov.trim <- function(object, which = c("imputed","model"), ... ) {
 #'
 #' @param z TRIM output structure (i.e., output of a call to \code{trim})
 #'
-#' @return a data.frame, one row per site-time combination, with columns for
+#' @return A data.frame, one row per site-time combination, with columns for
 #' site, time, observed counts, modelled counts and imputed counts.
 #' Missing observations are marked as NA
 #'

pkg/R/trim_wald.R

@@ -46,7 +46,7 @@
 #'
 #' @param x TRIM output structure (i.e., output of a call to \code{\link{trim}})
 #'
-#' @return a model-dependent list of Wald statistics
+#' @return A model-dependent list of Wald statistics
 #' @export
 #'
 #' @family analyses