CVP_RIDGEc

sample size for X_valid (used to calculate CV_error)

pxp sample covariance matrix for training data (denominator n).

S_train

pxp sample covariance matrix for validation data (denominator n).

S_valid

positive tuning parameters for ridge penalty. If a vector of parameters is provided, they should be in increasing order.

option to display progress of CV. Choose one of <code>progress</code> to print a progress bar, <code>print</code> to print completed tuning parameters, or <code>none</code>.

trace

Cross validation (no folds) function for RIDGEsigma. This function is to be used with CVP_RIDGE.

internal

Estimates a penalized precision matrix via the alternating direction method of multipliers (ADMM) algorithm. It currently supports a general elastic-net penalty that allows for both ridge and lasso-type penalties as special cases. This package is an alternative to the 'glasso' package.
See Boyd et al (2010) <doi:10.1561/2200000016> for details regarding the estimation method.

CVP_RIDGEc: CV (no folds) RIDGE penalized precision matrix estimation (c++)

Description

Usage

Arguments

Value