Make it examples take less time (than forever)

R/h.r

@@ -27,15 +27,16 @@
 #'   needed (i.e. the estimate is on the lower bounds), a warning is thrown.
 #' @export
 #' @examples
+#' \donttest{
 #' x <- rchallenge(1e4)
 #' xsum <- condense(bin(x, 1 / 10))
-#' h <- best_h(xsum, control = list(trace = 1, REPORT = 1))
-#' h <- best_h(xsum)
+#' h <- best_h(xsum, control = list(trace = 3, REPORT = 1))
 #'
 #' if (require("ggplot2")) {
 #' autoplot(xsum)
 #' autoplot(smooth(xsum, h))
 #' }
+#' }
 best_h <- function(x, h_init = NULL, ..., tol = 1e-2, control = list()) {
   stopifnot(is.condensed(x))
 

R/rmse.r

@@ -12,6 +12,7 @@
 #' @family bandwidth estimation functions
 #' @export
 #' @examples
+#' \donttest{
 #' set.seed(1014)
 #' # 1d -----------------------------
 #' x <- rchallenge(1e4)
@@ -33,6 +34,7 @@
 #' if (require("ggplot2")) {
 #' qplot(x, y, data = cvs, size = err)
 #' }
+#' }
 rmse_cvs <- function(x, hs = h_grid(x), ...) {
   rmse_1 <- function(i) {
     rmse_cv(x, as.numeric(hs[i, ]), ...)

man/best_h.Rd

@@ -41,16 +41,17 @@ of bandwidth makes little difference visually, and we're unlikely to have
 sufficient data to make a statistically significant choice anyway.
 }
 \examples{
+\donttest{
 x <- rchallenge(1e4)
 xsum <- condense(bin(x, 1 / 10))
-h <- best_h(xsum, control = list(trace = 1, REPORT = 1))
-h <- best_h(xsum)
+h <- best_h(xsum, control = list(trace = 3, REPORT = 1))
 
 if (require("ggplot2")) {
 autoplot(xsum)
 autoplot(smooth(xsum, h))
 }
 }
+}
 \seealso{
 Other bandwidth estimation functions: \code{\link{h_grid}};
   \code{\link{rmse_cv}}, \code{\link{rmse_cvs}}

man/rmse_cvs.Rd

@@ -25,6 +25,7 @@ bandwidths, \code{rmse_cvs} computes for a multiple vectors of bandwidths,
 stored as a data frame.
 }
 \examples{
+\donttest{
 set.seed(1014)
 # 1d -----------------------------
 x <- rchallenge(1e4)
@@ -47,6 +48,7 @@ if (require("ggplot2")) {
 qplot(x, y, data = cvs, size = err)
 }
 }
+}
 \seealso{
 Other bandwidth estimation functions: \code{\link{best_h}};
   \code{\link{h_grid}}