iilasso (version 0.0.1)

covCdaC: Optimize a linear regression model by coordinate descent algorithm using a covariance matrix

Description

Optimize a linear regression model by coordinate descent algorithm using a covariance matrix

Usage

covCdaC(Gamma, gamma, lambda, R, init_beta, delta = 0, maxit = 10000,
  eps = 1e-04, warm = "lambda", strong = TRUE)

Arguments

Gamma

covariance matrix of explanatory variables

gamma

covariance vector of explanatory and objective variables

lambda

lambda sequence

R

matrix using exclusive penalty term

init_beta

initial values of beta

delta

ratio of regularization between l1 and exclusive penalty terms

maxit

max iteration

eps

convergence threshold for optimization

warm

warm start direction: "lambda" (default) or "delta"

strong

whether use strong screening or not

Value

standardized beta