prepare_data_gaussian_cpp: Generate Gaussian MC samples

In NorskRegnesentral/shapr: Prediction Explanation with Dependence-Aware Shapley Values

Generate Gaussian MC samples

Description

Generate Gaussian MC samples

Usage

prepare_data_gaussian_cpp(MC_samples_mat, x_explain_mat, S, mu, cov_mat)

Arguments

MC_samples_mat	arma::mat. Matrix of dimension (n_samples, n_features) containing samples from the univariate standard normal.
x_explain_mat	arma::mat. Matrix of dimension (n_explain, n_features) containing the observations to explain.
S	arma::mat. Matrix of dimension (n_combinations, n_features) containing binary representations of the used coalitions. S cannot contain the empty or grand coalition, i.e., a row containing only zeros or ones. This is not a problem internally in shapr as the empty and grand coalitions treated differently.
mu	arma::vec. Vector of length n_features containing the mean of each feature.
cov_mat	arma::mat. Matrix of dimension (n_features, n_features) containing the pairwise covariance between all pairs of features.

Value

An arma::cube/3D array of dimension (n_samples, n_explain * n_coalitions, n_features), where the columns (,j,) are matrices of dimension (n_samples, n_features) containing the conditional Gaussian MC samples for each explicand and coalition.

Author(s)

Lars Henry Berge Olsen

NorskRegnesentral/shapr documentation built on April 19, 2024, 1:19 p.m.