jpen: JPEN Estimate of covariance matrix

In JPEN: Covariance and Inverse Covariance Matrix Estimation Using Joint Penalty

Description

Estimate of covariance Matrix using Joint Penalty Method

Usage

jpen(S,  gam, lam=NULL)

Arguments

S	Sample covariance matrix.
gam	Tuning parameter gamma. gam is non-negative.
lam	Tuning parameter lambda. lam is non-negative.

Details

This function returns an estimate of covariance matrix using Joint Penalty method.

Value

Estimate of Covariance Matrix.

Author(s)

Ashwini Maurya, Email: [e-mail]

References

A Well Conditioned and Sparse Estimate of Covariance and Inverse Covariance Matrix Using Joint Penalty. Submitted. http://arxiv.org/pdf/1412.7907v2.pdf

See Also

jpen.tune, jpen.inv

Examples

p=10;n=100;
Sig=diag(p);
y=rmvnorm(n,mean=rep(0,p),sigma=Sig);
gam=1.0;S=var(y);
lam=2/p;
Sighat=jpen(S,gam,lam);

JPEN documentation built on May 2, 2019, 5:54 a.m.