computeLambdaMax: computeLambdaMax

In thepira/cv.glmmLasso: Cross-validation for multi-level lasso

computeLambdaMax

Description

compute the maximum lambda value based on given dataset

Usage

computeLambdaMax(fix, rnd, data, scale = TRUE)

Arguments

fix	A two-sided linear formula object describing the fixed-effects part of the model, with the response on the left of a ~ operator and the terms, separated by + operators, on the right. For categorical covariables use as.factor(.) in the formula. Note, that the corresponding dummies are treated as a group and are updated blockwise
rnd	A two-sided linear formula object describing the random-effects part of the model, with the grouping factor on the left of a ~ operator and the random terms, separated by + operators, on the right; aternatively, the random effects design matrix can be given directly (with suitable column names). If set to NULL, no random effects are included.
data	The data frame containing the variables named in formula.
scale	default value is true

Details

lambdaMax is computed based on the coordinate descent algorithm from this paper: Friedman, Jerome, Trevor Hastie, and Rob Tibshirani. "Regularization paths for generalized linear models via coordinate descent."

Value

returns the lambdaMax value based on given dataset

Author(s)

Pirapong Jitngamplang, Jared Lander

thepira/cv.glmmLasso documentation built on Dec. 11, 2022, 11:20 p.m.