reduce example runtime

Author: tnagler

R/cpit.R

@@ -14,9 +14,9 @@
 #' set.seed(1)
 #' }
 #' # simulate data
-#' x <- matrix(rnorm(500), 250, 2)
+#' x <- matrix(rnorm(200), 100, 2)
 #' y <- x %*% c(1, -2)
-#' dat <- data.frame(y = y, x = x, z = as.factor(rbinom(250, 2, 0.5)))
+#' dat <- data.frame(y = y, x = x, z = as.factor(rbinom(100, 2, 0.5)))
 #'
 #' # fit vine regression model
 #' fit <- vinereg(y ~ ., dat)
@@ -44,9 +44,9 @@ cpit <- function(object, newdata, cores = 1) {
 #' set.seed(1)
 #' }
 #' # simulate data
-#' x <- matrix(rnorm(500), 250, 2)
+#' x <- matrix(rnorm(200), 100, 2)
 #' y <- x %*% c(1, -2)
-#' dat <- data.frame(y = y, x = x, z = as.factor(rbinom(250, 2, 0.5)))
+#' dat <- data.frame(y = y, x = x, z = as.factor(rbinom(100, 2, 0.5)))
 #'
 #' # fit vine regression model
 #' fit <- vinereg(y ~ ., dat)
@@ -81,9 +81,9 @@ cll <- function(object, newdata, cores = 1) {
 #' set.seed(1)
 #' }
 #' # simulate data
-#' x <- matrix(rnorm(500), 250, 2)
+#' x <- matrix(rnorm(200), 100, 2)
 #' y <- x %*% c(1, -2)
-#' dat <- data.frame(y = y, x = x, z = as.factor(rbinom(250, 2, 0.5)))
+#' dat <- data.frame(y = y, x = x, z = as.factor(rbinom(100, 2, 0.5)))
 #'
 #' # fit vine regression model
 #' fit <- vinereg(y ~ ., dat)