gconcord (version 0.41)

symlasso: Symmetric Lasso (symlasso)

Description

Estimates a sparse inverse covariance matrix from a pseudo-likelihood function formulation with L1 penalty on inverse covariance elements.

Usage

symlasso(data, lambda, tol = 1e-05, maxit = 100, save.iterates = FALSE, ...)

Arguments

data

Data matrix with n observations (rows) and p variables (columns)

lambda

Penalty parameter

tol

Convergence threshold

maxit

Maximum number of iterations before termination

save.iterates

Returns iterates if TRUE

...

ignored

Details

Implements the Symmetric Lasso method by Friedman, Hastie and Tibshirani (2010) http://statweb.stanford.edu/~tibs/ftp/ggraph.pdf

Examples

library(mvtnorm)

## True omega
omega <- matrix(0,3,3)
omega[1,2] <- omega[2,3] <- 2.1
omega <- t(omega) + omega
diag(omega) <- 3

sigma <- solve(omega)

## Generate data
set.seed(60)
data <- rmvnorm(100, rep(0,3), sigma)

## Solve
symlasso(data,2.1)