Regularized estimate of predictors covariance matrix.

This function computes a regularized version of the covariance matrix of the predictors. Among the possible models the one which maximizes BIC is returned.

Usage

msir.regularizedSigma(x, inv = FALSE, model = c("XII", "XXI", "XXX"))

Arguments

x

Ahe predictors data matrix.

inv

A logical specifying what must be returned. If TRUE the inverse of the estimated covariance matrix is returned, otherwise the estimated covariance matrix (default).

model

A character string specifying the available models:

• XII: diagonal equal variances

• XXI: diagonal unequal variances

• XXX: full covariance matrix

Value

A \((p \times p)\) covariance matrix estimate.

Author

Luca Scrucca luca.scrucca@unipg.it

See also

msir