examplesIf

R/model_performance.mixed.R

@@ -35,11 +35,9 @@
 #'   on returned indices.
 #' }
 #'
-#' @examples
-#' if (require("lme4")) {
-#'   model <- lmer(Petal.Length ~ Sepal.Length + (1 | Species), data = iris)
-#'   model_performance(model)
-#' }
+#' @examplesIf require("lme4")
+#' model <- lme4::lmer(Petal.Length ~ Sepal.Length + (1 | Species), data = iris)
+#' model_performance(model)
 #' @export
 model_performance.merMod <- function(model,
                                      metrics = "all",

R/performance_rmse.R

@@ -20,16 +20,15 @@
 #'
 #' @return Numeric, the root mean squared error.
 #'
-#' @examples
-#' if (require("nlme")) {
-#'   m <- lme(distance ~ age, data = Orthodont)
+#' @examplesIf require("nlme")
+#' data(Orthodont, package = "nlme")
+#' m <- nlme::lme(distance ~ age, data = Orthodont)
 #'
-#'   # RMSE
-#'   performance_rmse(m, normalized = FALSE)
+#' # RMSE
+#' performance_rmse(m, normalized = FALSE)
 #'
-#'   # normalized RMSE
-#'   performance_rmse(m, normalized = TRUE)
-#' }
+#' # normalized RMSE
+#' performance_rmse(m, normalized = TRUE)
 #' @export
 performance_rmse <- function(model, normalized = FALSE, verbose = TRUE) {
   tryCatch(

R/performance_score.R

@@ -32,7 +32,7 @@
 #'
 #' @seealso [`performance_logloss()`]
 #'
-#' @examples
+#' @examplesIf require("glmmTMB")
 #' ## Dobson (1990) Page 93: Randomized Controlled Trial :
 #' counts <- c(18, 17, 15, 20, 10, 20, 25, 13, 12)
 #' outcome <- gl(3, 1, 9)
@@ -41,17 +41,15 @@
 #'
 #' performance_score(model)
 #' \dontrun{
-#' if (require("glmmTMB")) {
-#'   data(Salamanders)
-#'   model <- glmmTMB(
-#'     count ~ spp + mined + (1 | site),
-#'     zi = ~ spp + mined,
-#'     family = nbinom2(),
-#'     data = Salamanders
-#'   )
+#' data(Salamanders, package = "glmmTMB")
+#' model <- glmmTMB::glmmTMB(
+#'   count ~ spp + mined + (1 | site),
+#'   zi = ~ spp + mined,
+#'   family = nbinom2(),
+#'   data = Salamanders
+#' )
 #'
-#'   performance_score(model)
-#' }
+#' performance_score(model)
 #' }
 #' @export
 performance_score <- function(model, verbose = TRUE, ...) {