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R/convert_bayesian_to_frequentist.R

@@ -8,38 +8,33 @@
 #' @param REML For mixed effects, should models be estimated using
 #'   restricted maximum likelihood (REML) (`TRUE`, default) or maximum
 #'   likelihood (`FALSE`)?
-#' @examples
+#' @examplesIf require("rstanarm")
 #' \donttest{
 #' # Rstanarm ----------------------
-#' if (require("rstanarm")) {
-#'   # Simple regressions
-#'   model <- stan_glm(Sepal.Length ~ Species,
-#'     data = iris, chains = 2, refresh = 0
-#'   )
-#'   bayesian_as_frequentist(model)
-#' }
-#' }
+#' # Simple regressions
+#' model <- rstanarm::stan_glm(Sepal.Length ~ Species,
+#'   data = iris, chains = 2, refresh = 0
+#' )
+#' bayesian_as_frequentist(model)
 #'
-#' \donttest{
-#' if (require("rstanarm")) {
-#'   model <- stan_glm(vs ~ mpg,
-#'     family = "binomial",
-#'     data = mtcars, chains = 2, refresh = 0
-#'   )
-#'   bayesian_as_frequentist(model)
+#' model <- rstanarm::stan_glm(vs ~ mpg,
+#'   family = "binomial",
+#'   data = mtcars, chains = 2, refresh = 0
+#' )
+#' bayesian_as_frequentist(model)
 #'
-#'   # Mixed models
-#'   model <- stan_glmer(Sepal.Length ~ Petal.Length + (1 | Species),
-#'     data = iris, chains = 2, refresh = 0
-#'   )
-#'   bayesian_as_frequentist(model)
+#' # Mixed models
+#' model <- rstanarm::stan_glmer(
+#'   Sepal.Length ~ Petal.Length + (1 | Species),
+#'   data = iris, chains = 2, refresh = 0
+#' )
+#' bayesian_as_frequentist(model)
 #'
-#'   model <- stan_glmer(vs ~ mpg + (1 | cyl),
-#'     family = "binomial",
-#'     data = mtcars, chains = 2, refresh = 0
-#'   )
-#'   bayesian_as_frequentist(model)
-#' }
+#' model <- rstanarm::stan_glmer(vs ~ mpg + (1 | cyl),
+#'   family = "binomial",
+#'   data = mtcars, chains = 2, refresh = 0
+#' )
+#' bayesian_as_frequentist(model)
 #' }
 #'
 #' @export