Add more returns and examples for docs

R/bootstrap-dea.R

@@ -6,11 +6,11 @@ NULL
 #' Run bootstrap on a DEA model to estimate bias corrected efficiency scores and confidence
 #' intervals
 #'
-#' @param dea An object of type pioneer_dea from `compute_dea()`
-#' @param alpha One minus the confidence level required (defaults to 0.05)
+#' @param dea An object of class 'pioneer_dea' from `compute_dea()`
+#' @param alpha One minus the confidence level required. Default is 0.05.
 #' @param bw_rule A string with the type of bandwidth rule to be used, or a number with the
 #'   bandwidth parameter. See details.
-#' @param iterations The number of bootstrap iterations to be performed
+#' @param iterations Integer. The number of bootstrap iterations to perform. Default is 2000.
 #'
 #' @details
 #' In order to bootstrap a DEA model, you must first create a DEA model object using the
@@ -25,16 +25,18 @@ NULL
 #' applications of the bootstrap, the default of unbias cross validation is sensible.
 #'
 #' @examples
-#' \dontrun{
 #' # Get data
 #' fare89 <- deaR::Electric_plants
 #' # Estimate efficiency
-#' mod <- compute_dea(fare89, 'Plant', c('Labor', 'Fuel', 'Capital'), 'Output', 'vrs', 'in')
-#' # Run bootstrap
-#' boot <- bootstrap_dea(mod, iterations = 2000)
-#' }
+#' mod <- compute_dea(fare89,
+#'   input = c("Labor", "Fuel", "Capital"),
+#'   output = "Output",
+#'   id = "Plant",
+#' )
+#' # Run bootstrap. Reducing the number of iterations to save processing time
+#' boot <- bootstrap_dea(mod, iterations = 100)
 #'
-#' @return A list object of class `pioneer_bootstrap`
+#' @return An object of class 'pioneer_bootstrap' containing bootstrap results.
 #' @seealso [compute_dea()]
 #'
 #' @export

R/compute_dea.R

@@ -19,6 +19,20 @@
 #' @param slack If `TRUE` slack values are calculated.
 #' @param peers If `TRUE` peers are added to the response.
 #'
+#' @examples
+#' # Get data
+#' fare89 <- deaR::Electric_plants
+#' # Estimate efficiency
+#' mod <- compute_dea(fare89,
+#'   input = c("Labor", "Fuel", "Capital"),
+#'   output = "Output",
+#'   id = "Plant",
+#'   rts = "vrs",
+#'   orientation = "in"
+#' )
+#' # Print the results
+#' print(mod)
+#'
 #' @return A list of class `pioneer_dea`
 #' @export
 compute_dea <- function(

R/dea-utils.R

@@ -3,10 +3,17 @@
 #' Create a matrix for input or output variables that can be used in DEA models
 #' from a supplied data.frame
 #'
-#' @param df A data.frame
-#' @param columns A vector of column names that should be included in the matrix
-#' @param id The name of the column with the DMU IDs
-#' @param normalize If `TRUE`, all columns will be normalized with a mean of 1
+#' @param df A data.frame containing the data.
+#' @param columns A character vector of column names to include in the matrix.
+#' @param id A character string specifying the column with DMU IDs.
+#' @param normalize A logical indicating whether to normalize the columns by their
+#'   mean. Defaults to `FALSE`.
+#'
+#' @examples
+#' df <- data.frame(id = 1:3, a = c(10, 20, 30), b = c(5, 15, 25))
+#' create_matrix(df, columns = c("a", "b"), id = "id", normalize = TRUE)
+#'
+#' @return A matrix of inputs or outputs
 #'
 #' @export
 create_matrix <- function(df, columns, id, normalize = FALSE) {
@@ -37,6 +44,17 @@ create_matrix <- function(df, columns, id, normalize = FALSE) {
 #' @param digits An integer with the number of digits to round to. If `NULL` the
 #'   values are kept unrounded.
 #'
+#' @examples
+#' # Create matrices with random values
+#' inputs <- matrix(runif(10, 1, 10), ncol = 2)
+#' outputs <- matrix(runif(10, 1, 10), ncol = 2)
+#' # Compute scale efficiency
+#' compute_scale_efficiency(inputs, outputs, orientation = 'out', digits = 2)
+#'
+#' @return A data frame containing the efficiency scores for CRS, VRS, the
+#'   Scale Efficiency, the VRS to NIRS ratio, and a recommendation on whether to
+#'   increase or decrease the size of the DMU.
+#'
 #' @export
 compute_scale_efficiency <- function(
     x,

R/shiny-functions.R

@@ -58,17 +58,13 @@ run_pioneer <- function(x = NULL, port = NULL, ...) {
 
 }
 
-#' @rdname run_pioneer
-#' @export
-runPioneeR <- function(x = NULL, port = NULL, ...) {
-  deprecation_warning(alternative = "run_pioneeR", next_release = TRUE)
-  run_pioneer(x = x, port = port, ...)
-}
-
 #' Unset environment variables
 #'
 #' Unsets the environment variables set by pioneeR
 #'
+#' @examples
+#' unset_env_vars()
+#'
 #' @export
 unset_env_vars <- \() Sys.unsetenv('PIONEER_DATA')