Generate null samples for Gaussian copula covariates

This function generates null samples of a given subset of variables for Gaussian copula covariates.

sample.g_copula.nulls(X, S, K, gamma_X.list_S, sigma_X.list_S, verbose = FALSE)

Arguments

X	a n by p matrix, containing the Gaussian vectors before applying the probability integral transform
S	a subset of covariates, for which null samples are constructed.
K	number of null replicates.
gamma_X.list_S	a list of length \|S\|, with each element being the linear coefficient of the given covariate on the other covariates (before the probability integral transform).
sigma_X.list_S	a list of length \|S\|, with each element being the variance of the conditional distribution (before the probability integral transform).
verbose	whether to show intermediate progress (default: FALSE).

A list of length |S|, with each element being a (n*K)-dimensional vector, which contains K set of null samples.

Zhang L, Janson L (2020). “Floodgate: Inference for Model-Free Variable Importance.” arXiv preprint arXiv:2007.01283.