Nothing
#' Interaction Difference Test for Prediction Models
#'
#' Provides functions to conduct a model-agnostic asymptotic
#' hypothesis test for the identification of interaction effects in
#' black-box machine learning models. The null hypothesis assumes that a given
#' set of covariates does not contribute to interaction effects in the prediction
#' model. The test statistic is based on the difference of variances of
#' partial dependence functions with respect to the original
#' black-box predictions and the predictions under the null hypothesis.
#' The hypothesis test can be applied to any black-box prediction model,
#' and the null hypothesis of the test can be flexibly specified according
#' to the research question of interest. Furthermore, the test is computationally
#' fast to apply as the null distribution does not require resampling or
#' refitting black-box prediction models.
#'
#' \tabular{ll}{ Package: \tab IADT \cr Type: \tab Package \cr Version:
#' \tab 1.2.1 \cr Date: \tab 2024-05-14 \cr License: \tab GPL-3 \cr }
#'
#' @name IADT-package
#' @aliases IADT-package
#' @docType package
#' @author Thomas Welchowski \email{welchow@@imbie.meb.uni-bonn.de}
#' @references
#' \insertRef{welchowskiIntroIML}{IADT} \cr\cr
#' \insertRef{friedmanInteract}{IADT}
#' @keywords package
NULL
# Namespace code
#' @importFrom Rmpfr mpfr mean pnorm
#' @importFrom methods new
#' @importFrom parallel makeCluster clusterExport clusterEvalQ parLapplyLB stopCluster
#' @importFrom stats predict sd
#' @importFrom mgcv gam
#' @importFrom Rdpack reprompt
#' @importFrom utils sessionInfo
#' @importFrom mvnfast rmvn
NULL
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.