examples

R/looic.R

@@ -12,6 +12,7 @@
 #' @return A list with four elements, the ELPD, LOOIC and their standard errors.
 #'
 #' @examplesIf require("rstanarm")
+#' \donttest{
 #' model <- suppressWarnings(rstanarm::stan_glm(
 #'   mpg ~ wt + cyl,
 #'   data = mtcars,
@@ -20,6 +21,7 @@
 #'   refresh = 0
 #' ))
 #' looic(model)
+#' }
 #' @export
 looic <- function(model, verbose = TRUE) {
   insight::check_if_installed("loo")

R/r2_bayes.R

@@ -30,67 +30,63 @@
 #'   `r2_posterior()` is the actual workhorse for `r2_bayes()` and
 #'   returns a posterior sample of Bayesian R2 values.
 #'
-#' @examples
+#' @examplesIf require("rstanarm") && require("rstantools") && require("BayesFactor") && require("brms")
 #' library(performance)
-#' if (require("rstanarm") && require("rstantools")) {
-#'   model <- suppressWarnings(stan_glm(
-#'     mpg ~ wt + cyl,
-#'     data = mtcars,
-#'     chains = 1,
-#'     iter = 500,
-#'     refresh = 0,
-#'     show_messages = FALSE
-#'   ))
-#'   r2_bayes(model)
+#' \donttest{
+#' model <- suppressWarnings(rstanarm::stan_glm(
+#'   mpg ~ wt + cyl,
+#'   data = mtcars,
+#'   chains = 1,
+#'   iter = 500,
+#'   refresh = 0,
+#'   show_messages = FALSE
+#' ))
+#' r2_bayes(model)
 #'
-#'   model <- suppressWarnings(stan_lmer(
-#'     Petal.Length ~ Petal.Width + (1 | Species),
-#'     data = iris,
-#'     chains = 1,
-#'     iter = 500,
-#'     refresh = 0
-#'   ))
-#'   r2_bayes(model)
+#' model <- suppressWarnings(rstanarm::stan_lmer(
+#'   Petal.Length ~ Petal.Width + (1 | Species),
+#'   data = iris,
+#'   chains = 1,
+#'   iter = 500,
+#'   refresh = 0
+#' ))
+#' r2_bayes(model)
 #' }
 #'
-#' if (require("BayesFactor")) {
-#'   BFM <- generalTestBF(mpg ~ qsec + gear, data = mtcars, progress = FALSE)
-#'   FM <- lmBF(mpg ~ qsec + gear, data = mtcars)
+#' BFM <- BayesFactor::generalTestBF(mpg ~ qsec + gear, data = mtcars, progress = FALSE)
+#' FM <- BayesFactor::lmBF(mpg ~ qsec + gear, data = mtcars)
 #'
-#'   r2_bayes(FM)
-#'   r2_bayes(BFM[3])
-#'   r2_bayes(BFM, average = TRUE) # across all models
+#' r2_bayes(FM)
+#' r2_bayes(BFM[3])
+#' r2_bayes(BFM, average = TRUE) # across all models
 #'
-#'   # with random effects:
-#'   mtcars$gear <- factor(mtcars$gear)
-#'   model <- lmBF(
-#'     mpg ~ hp + cyl + gear + gear:wt,
-#'     mtcars,
-#'     progress = FALSE,
-#'     whichRandom = c("gear", "gear:wt")
-#'   )
+#' # with random effects:
+#' mtcars$gear <- factor(mtcars$gear)
+#' model <- BayesFactor::lmBF(
+#'   mpg ~ hp + cyl + gear + gear:wt,
+#'   mtcars,
+#'   progress = FALSE,
+#'   whichRandom = c("gear", "gear:wt")
+#' )
 #'
-#'   r2_bayes(model)
-#' }
+#' r2_bayes(model)
 #'
 #' \donttest{
-#' if (require("brms")) {
-#'   model <- suppressWarnings(brms::brm(
-#'     mpg ~ wt + cyl,
-#'     data = mtcars,
-#'     silent = 2,
-#'     refresh = 0
-#'   ))
-#'   r2_bayes(model)
+#' model <- suppressWarnings(brms::brm(
+#'   mpg ~ wt + cyl,
+#'   data = mtcars,
+#'   silent = 2,
+#'   refresh = 0
+#' ))
+#' r2_bayes(model)
 #'
-#'   model <- suppressWarnings(brms::brm(
-#'     Petal.Length ~ Petal.Width + (1 | Species),
-#'     data = iris,
-#'     silent = 2,
-#'     refresh = 0
-#'   ))
-#'   r2_bayes(model)
-#' }
+#' model <- suppressWarnings(brms::brm(
+#'   Petal.Length ~ Petal.Width + (1 | Species),
+#'   data = iris,
+#'   silent = 2,
+#'   refresh = 0
+#' ))
+#' r2_bayes(model)
 #' }
 #' @references
 #' Gelman, A., Goodrich, B., Gabry, J., and Vehtari, A. (2018).