Delete some time-consuming examples to meet cran requirements.

R/evaluation.R

@@ -37,25 +37,6 @@
 #' @importFrom stats median
 #' @importFrom microbenchmark microbenchmark
 #' @export
-#' @examples
-#' library(latentcor)
-#' grid_list = list(LatentR = seq(-0.5, 0.5, by = 0.5), TruncRate = seq(0.1, 0.9, by = 0.4))
-#' genfun = function (grid_input, ...) {
-#'   out = gen_data(rhos = grid_input[1], XP = list(grid_input[2], NA), ...)$X
-#'   return(out)
-#' }
-#' estfun_1 = function(X, ...) {
-#'   out = latentcor(X = X, method = "original", ...)$R[1, 2]
-#'   return(out)
-#' }
-#' estfun_2 = function(X, ...) {
-#'   out = latentcor(X = X, method = "approx", ...)$R[1, 2]
-#'   return(out)
-#' }
-#'evaluation_BC = evaluation(genfun = genfun, estfun_1 = estfun_1, estfun_2 = estfun_2,
-#' grid_list = grid_list, nrep = 2, showplot = FALSE, types = c("bin", "con"))
-#'evaluation_BC$meanAE_diff
-#'evaluation_BC$plot_meanAE_diff
 
 evaluation = function(genfun, estfun_1, estfun_2, grid_list, nrep = 100, showplot = FALSE, cores = detectCores(), ...) {
   grid_all = expand.grid(grid_list)

R/interpolation.R

@@ -16,7 +16,7 @@
 #' @importFrom parallel detectCores
 #' @export
 #' @examples
-#' grid_list = list(seq(-0.9, 0.9, by = 0.1), seq(0.1, 0.9, by = 0.1))
+#' grid_list = list(seq(-0.5, 0.5, by = 0.5), seq(-0.5, 0.5, by = 0.5))
 #' objfun = function(x, y) {x^2 + sqrt(y)}
 #' evalfun = function(X) {objfun(X[1], X[2])}
 #' value = interpolation(evalfun = evalfun, grid_list = grid_list)$value