scio.cv: Sparse Column-wise Inverse Operator

In scio: Sparse Columnwise Inverse Operator

Description

Cross validated estimates of a sparse inverse covariance matrix using Sparse Column-wise Inverse Operator

Usage

scio.cv(X, lambda.max=1, alpha=0.95, cv.maxit=1e2, ...)

Arguments

X	Input data of dimension samples (n) x variables (p).
lambda.max	Maximum lambda to start with in CV, which is decreased by mutliplying alpha in each iteration.
alpha	Scaling factor to decrease lambda by multiplication.
cv.maxit	Maximum number of CV iterations. Default 1e2.
...	Other option parameters in scio.

Details

This is a fast, nonparametric approach to estimate sparse inverse covariance matrices, with possibly really large dimensions. Details of this procedure are described in the reference.

This function does a simple cross validation based on likelihood.

Value

A list with components:

w	Estimated inverse covariance matrix
lambda.cv	CV selected lambda

References

Weidong Liu and Xi Luo (2012). Fast and Adaptive Sparse Precision Matrix Estimation in High Dimensions. arXiv:1203.3896.

Examples

set.seed(100)
x<-matrix(rnorm(50*20),ncol=4)
a<-scio.cv(x)

Example output

scio documentation built on March 3, 2020, 1:07 a.m.