This function computes a regularized version of the covariance matrix of the predictors. Among the possible models the one which maximizes BIC is returned.
msir.regularizedSigma(x, inv = FALSE, model = c("XII", "XXI", "XXX"))Ahe predictors data matrix.
A logical specifying what must be returned. If TRUE the inverse of the estimated covariance matrix is returned, otherwise the estimated covariance matrix (default).
A character string specifying the available models:
XII: diagonal equal variances
XXI: diagonal unequal variances
XXX: full covariance matrix
A \((p \times p)\) covariance matrix estimate.