Generate (Gaussian) Copula MC samples
prepare_data_copula_cpp(
MC_samples_mat,
x_explain_mat,
x_explain_gaussian_mat,
x_train_mat,
S,
mu,
cov_mat
)An arma::cube/3D array of dimension (n_MC_samples, n_explain * n_coalitions, n_features), where
the columns (,j,) are matrices of dimension (n_MC_samples, n_features) containing the conditional Gaussian
copula MC samples for each explicand and coalition on the original scale.
arma::mat.
Matrix of dimension (n_MC_samples, n_features) containing samples from the univariate standard normal.
arma::mat.
Matrix of dimension (n_explain, n_features) containing the observations to explain.
arma::mat.
Matrix of dimension (n_explain, n_features) containing the observations to explain after being transformed
using the Gaussian transform, i.e., the samples have been transformed to a standardized normal distribution.
arma::mat.
Matrix of dimension (n_train, n_features) containing the training observations.
arma::mat.
Matrix of dimension (n_coalitions, 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 are treated differently.
arma::vec.
Vector of length n_features containing the mean of each feature after being transformed using the Gaussian
transform, i.e., the samples have been transformed to a standardized normal distribution.
arma::mat.
Matrix of dimension (n_features, n_features) containing the pairwise covariance between all pairs of features
after being transformed using the Gaussian transform, i.e., the samples have been transformed to a standardized
normal distribution.
Lars Henry Berge Olsen