symlasso: Symmetric Lasso (symlasso)

In gconcord: Concord method for Graphical Model Selection

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)

gconcord documentation built on May 2, 2019, 7:30 a.m.