Merge pull request #69 from jhorzek/update_documentation

updated documentation of return values

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: mxsem
 Type: Package
 Title: Specify 'OpenMx' Models with a 'lavaan'-Style Syntax
-Version: 0.0.10
+Version: 0.1.0
 Authors@R: c(person(given   = "Jannik H.", family = "Orzek",
                     role    = c("aut", "cre", "cph"),
                     email   = "[email protected]",
@@ -20,7 +20,7 @@ Imports:
   dplyr,
   utils
 LinkingTo: Rcpp
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Encoding: UTF-8
 Suggests:
     knitr,

R/check_modifier_for_algebra.R

@@ -6,7 +6,7 @@
 #' @param parameter_table parameter table
 #' @param directed symbol used to indicate directed effects (regressions and loadings)
 #' @param undirected symbol used to indicate undirected effects (variances and covariances)
-#' @return parameter_table
+#' @returns data.frame with parameters (parameter table)
 #' @keywords internal
 check_modifier_for_algebra <- function(parameter_table,
                                        directed,

R/extract_algebra_elements.R

@@ -3,7 +3,7 @@
 #' extract all variables/parameters from an mxAlgebra
 #' @param mxAlgebra_formula formula embedded in mxAlgebra
 #' @param extracted used in recursive function calls; don't set this manually
-#' @return vector with names of variables and parameters used in the function call
+#' @returns vector with names of variables and parameters used in the function call
 #' @keywords internal
 extract_algebra_elements <- function(mxAlgebra_formula, extracted = c()){
 

R/mxsem.R

@@ -211,7 +211,7 @@ NULL
 #' @param undirected symbol used to indicate undirected effects (variances and covariances)
 #' @param return_parameter_table if set to TRUE, the internal parameter table is returend
 #' together with the mxModel
-#' @return mxModel object that can be fitted with mxRun or mxTryHard. If return_parameter_table
+#' @returns mxModel object that can be fitted with mxRun or mxTryHard. If return_parameter_table
 #' is TRUE, a list with the mxModel and the parameter table is returned.
 #' @export
 #' @import OpenMx

R/mxsem_group_by.R

@@ -26,7 +26,7 @@
 #' group specific. For instance, if parameters = "a" and use_grepl = TRUE, all parameters
 #' whose label contains the letter "a" will be group specific. If use_grep = FALSE
 #' only the parameter that has the label "a" is group specific.
-#' @return mxModel with multiple groups. Use get_groups to extract the groups
+#' @returns mxModel with multiple groups. Use get_groups to extract the groups
 #' @export
 #' @examples
 #' # THE FOLLOWING EXAMPLE IS ADAPTED FROM
@@ -144,7 +144,7 @@ mxsem_group_by <- function(mxModel,
 #'
 #' returns a list of groups for a multi group model
 #' @param multi_group_model multi group model created with mxsem_group_by
-#' @return list with data for each group
+#' @returns list with data for each group
 #' @export
 #' @examples
 #' # THE FOLLOWING EXAMPLE IS ADAPTED FROM
@@ -228,6 +228,7 @@ summarize_multi_group_model <- function(multi_group_model){
 #' @param x object from summarize_multi_group_model
 #' @param ... not used
 #' @method print multi_group_parameters
+#' @returns nothing
 #' @export
 print.multi_group_parameters <- function(x, ...){
   console_width <- getOption("width")

R/set_starting_values.R

@@ -4,7 +4,7 @@
 #' omxSetParameters.
 #' @param mx_model model of class mxModel
 #' @param values vector with labeled parameter values
-#' @return mxModel with changed parameter values
+#' @returns mxModel with changed parameter values
 #' @export
 #' @examples
 #' library(mxsem)

R/simulate_data.R

@@ -4,7 +4,7 @@
 #' simulate data for a latent growth curve model with five measurement occasions.
 #' The time-distance between these occasions differs between subjects.
 #' @param N sample size
-#' @return data set with columns y1-y5 (observations) and t_1-t_5 (time of
+#' @returns data set with columns y1-y5 (observations) and t_1-t_5 (time of
 #' observation)
 #' @export
 #' @importFrom stats rnorm
@@ -51,7 +51,7 @@ simulate_latent_growth_curve <- function(N = 100){
 #'
 #' simulate data for a moderated nonlinear factor analysis.
 #' @param N sample size
-#' @return data set with variables x1-x3 and y1-y3 representing repeated measurements
+#' @returns data set with variables x1-x3 and y1-y3 representing repeated measurements
 #' of an affect measure. It is assumed that the autoregressive effect is different
 #' depending on covariate k
 #' @export

R/unicode_arrows.R

@@ -2,7 +2,7 @@
 #'
 #' this function returns the unicode for directed arrows
 #'
-#' @return returns unicode for directed arrows
+#' @returns returns unicode for directed arrows
 #' @export
 unicode_directed <- function()
   return("\u2192")
@@ -11,7 +11,7 @@ unicode_directed <- function()
 #'
 #' this function returns the unicode for undirected arrows
 #'
-#' @return returns unicode for undirected arrows
+#' @returns returns unicode for undirected arrows
 #' @export
 unicode_undirected <- function()
   return("\u2194")