spcov_bcd: Covariance Graphical Lasso

In dilernia/rcm: Implemention of Random Covariance Models

Description

This function implements the Random Covariance Model (RCM) for joint estimation of multiple sparse precision matrices. Optimization is conducted using block coordinate descent.

Usage

spcov_bcd(samp_cov, rho, initial = NULL)

Arguments

samp_cov	p x p sample covariance matrix.
rho	Non-negative scalar. Induces sparsity in covariance matrix.
initial	Initial value for covariance matrix.

Value

p x p sparse covariance matrix estimate.

References

Wang, Hao. "Two New Algorithms for Solving Covariance Graphical Lasso Based on Coordinate Descent and ECM." 2012. https://arxiv.org/pdf/1205.4120.pdf

dilernia/rcm documentation built on Aug. 11, 2020, 7:29 a.m.