msir.regularizedSigma: Regularized estimate of predictors covariance matrix.
Description
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
the predictors data matrix.
inv
if TRUE the inverse of the estimated covariance matrix is returned.
model
available models:
lcl{
XII = diagonal equal variances
XXI = diagonal unequal variances
XXX = full covariance matrix
}
Value
- A $(p \times p)$ covariance matrix estimate.