symlasso {gconcord} | R Documentation |
Estimates a sparse inverse covariance matrix from a pseudo-likelihood function formulation with L1 penalty on inverse covariance elements.
symlasso(data, lambda, tol = 1e-05, maxit = 100, save.iterates = FALSE, ...)
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 |
Implements the Symmetric Lasso method by Friedman, Hastie and Tibshirani (2010) http://statweb.stanford.edu/~tibs/ftp/ggraph.pdf
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)