Nothing
# --------------------------------------
# Author: Andreas Alfons
# Erasmus Universiteit Rotterdam
# --------------------------------------
#' Resampling-based prediction error for fitted models
#'
#' Generic function to estimate the prediction error of a fitted model via
#' (repeated) \eqn{K}-fold cross-validation, (repeated) random splitting (also
#' known as random subsampling or Monte Carlo cross-validation), or the
#' bootstrap.
#'
#' The idea is that developers write easy-to-use methods for end users to
#' leverage the prediction error estimation framework for their models. A
#' typical \code{perry} method consists of the following two parts: first the
#' data are extracted from the model, then function \code{\link{perryFit}} is
#' called to perform prediction error estimation. The programming effort of
#' implementing prediction error estimation for a certain model is thus greatly
#' reduced.
#'
#' Examples for methods are available in package perryExamples (see
#' \code{\link[perryExamples]{perry-methods}}).
#'
#' @param object the fitted model for which to estimate the prediction error.
#' @param \dots additional arguments to be passed down to methods.
#'
#' @author Andreas Alfons
#'
#' @seealso \code{\link{perryFit}}, \code{\link[perryExamples]{perry-methods}}
#'
#' @keywords utilities
#'
#' @export
perry <- function(object, ...) UseMethod("perry")
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.