prepare_data_copula_cpp {shapr} | R Documentation |
Generate (Gaussian) Copula MC samples
Description
Generate (Gaussian) Copula MC samples
Usage
prepare_data_copula_cpp(
MC_samples_mat,
x_explain_mat,
x_explain_gaussian_mat,
x_train_mat,
S,
mu,
cov_mat
)
Arguments
MC_samples_mat |
arma::mat.
Matrix of dimension (n_MC_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.
|
x_explain_gaussian_mat |
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.
|
x_train_mat |
arma::mat.
Matrix of dimension (n_train , n_features ) containing the training observations.
|
S |
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.
|
mu |
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.
|
cov_mat |
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.
|
Value
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.
Author(s)
Lars Henry Berge Olsen
[Package
shapr version 1.0.4
Index]