equal1: Non-symmetric version of EQUAL

In cescwang85/EQUAL: An efficient ADMM algorithm for high dimensional precision matrix estimation via penalized quadratic loss

Non-symmetric version of EQUAL

Description

ADMM algorithm for high precision matrix estimation using asymmetic loss

Usage

equal1(X, lambda, err = 10^(-5), maxIter = 1000L, rho = 1, diag = 0L)

Arguments

X	data matrix of dimension n*p.
lambda	user supplied tuning parameter;
err	the precision used to stop the convergence. Default is 1e-5. Iterations stop when average absolute parameter change is less than err.
maxIter	Maximum number of iterations. Default is 1000.
rho	step parameter for the ADMM. Default is 1.
diag	Should diagonal elements of the Matrix be thresholding? Default is FALSE.

Value

A list with components

Omega	a list of sparse p*p matrices corresponding to lambda.
lambda	the used lambda for the solution path.
niter	the number of iterations for each element of lambda.

cescwang85/EQUAL documentation built on Nov. 26, 2022, 1:27 a.m.