diff --git a/R/bootstrap-dea.R b/R/bootstrap-dea.R
index 0d85b46..31610ba 100644
--- a/R/bootstrap-dea.R
+++ b/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
diff --git a/R/compute_dea.R b/R/compute_dea.R
index 8754615..10072f8 100644
--- a/R/compute_dea.R
+++ b/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(
diff --git a/R/dea-utils.R b/R/dea-utils.R
index 3c57381..deb590d 100644
--- a/R/dea-utils.R
+++ b/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,
diff --git a/R/shiny-functions.R b/R/shiny-functions.R
index 532d9ea..8366535 100644
--- a/R/shiny-functions.R
+++ b/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')
 
diff --git a/man/bootstrap_dea.Rd b/man/bootstrap_dea.Rd
index ecbeb14..92b2314 100644
--- a/man/bootstrap_dea.Rd
+++ b/man/bootstrap_dea.Rd
@@ -7,17 +7,17 @@
 bootstrap_dea(dea, alpha = 0.05, bw_rule = "ucv", iterations = 2000)
 }
 \arguments{
-\item{dea}{An object of type pioneer_dea from \code{compute_dea()}}
+\item{dea}{An object of class 'pioneer_dea' from \code{compute_dea()}}
 
-\item{alpha}{One minus the confidence level required (defaults to 0.05)}
+\item{alpha}{One minus the confidence level required. Default is 0.05.}
 
 \item{bw_rule}{A string with the type of bandwidth rule to be used, or a number with the
 bandwidth parameter. See details.}
 
-\item{iterations}{The number of bootstrap iterations to be performed}
+\item{iterations}{Integer. The number of bootstrap iterations to perform. Default is 2000.}
 }
 \value{
-A list object of class \code{pioneer_bootstrap}
+An object of class 'pioneer_bootstrap' containing bootstrap results.
 }
 \description{
 Run bootstrap on a DEA model to estimate bias corrected efficiency scores and confidence
@@ -36,14 +36,16 @@ to replicate results where \code{h} is given, such as Simar & Wilson (1998). For
 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)
 
 }
 \seealso{
diff --git a/man/compute_dea.Rd b/man/compute_dea.Rd
index f5bd7b7..55808bb 100644
--- a/man/compute_dea.Rd
+++ b/man/compute_dea.Rd
@@ -48,3 +48,18 @@ A list of class \code{pioneer_dea}
 Solve an input or output oriented DEA model under constant (\code{crs}), variable (\code{vrs}),
 non-increasing (\code{drs}), or non-decreasing (\code{irs}) returns to scale.
 }
+\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)
+
+}
diff --git a/man/compute_scale_efficiency.Rd b/man/compute_scale_efficiency.Rd
index 70d1cfc..ccd55de 100644
--- a/man/compute_scale_efficiency.Rd
+++ b/man/compute_scale_efficiency.Rd
@@ -16,7 +16,20 @@ compute_scale_efficiency(x, y, orientation = c("in", "out"), digits = NULL)
 \item{digits}{An integer with the number of digits to round to. If \code{NULL} the
 values are kept unrounded.}
 }
+\value{
+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.
+}
 \description{
 Calculate scale efficiency from a set of inputs and outputs and return a
 data.frame
 }
+\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)
+
+}
diff --git a/man/create_matrix.Rd b/man/create_matrix.Rd
index 3564696..3c8e23f 100644
--- a/man/create_matrix.Rd
+++ b/man/create_matrix.Rd
@@ -7,15 +7,24 @@
 create_matrix(df, columns, id, normalize = FALSE)
 }
 \arguments{
-\item{df}{A data.frame}
+\item{df}{A data.frame containing the data.}
 
-\item{columns}{A vector of column names that should be included in the matrix}
+\item{columns}{A character vector of column names to include in the matrix.}
 
-\item{id}{The name of the column with the DMU IDs}
+\item{id}{A character string specifying the column with DMU IDs.}
 
-\item{normalize}{If \code{TRUE}, all columns will be normalized with a mean of 1}
+\item{normalize}{A logical indicating whether to normalize the columns by their
+mean. Defaults to \code{FALSE}.}
+}
+\value{
+A matrix of inputs or outputs
 }
 \description{
 Create a matrix for input or output variables that can be used in DEA models
 from a supplied data.frame
 }
+\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)
+
+}
diff --git a/man/run_pioneer.Rd b/man/run_pioneer.Rd
index 6e56a9f..8684a1c 100644
--- a/man/run_pioneer.Rd
+++ b/man/run_pioneer.Rd
@@ -2,12 +2,9 @@
 % Please edit documentation in R/shiny-functions.R
 \name{run_pioneer}
 \alias{run_pioneer}
-\alias{runPioneeR}
 \title{Run pioneeR}
 \usage{
 run_pioneer(x = NULL, port = NULL, ...)
-
-runPioneeR(x = NULL, port = NULL, ...)
 }
 \arguments{
 \item{x}{A data frame that should be loaded with the app. See details.}
diff --git a/man/unset_env_vars.Rd b/man/unset_env_vars.Rd
index dda6162..045f853 100644
--- a/man/unset_env_vars.Rd
+++ b/man/unset_env_vars.Rd
@@ -9,3 +9,7 @@ unset_env_vars()
 \description{
 Unsets the environment variables set by pioneeR
 }
+\examples{
+unset_env_vars()
+
+}