lassoModel: Lasso Model Generation

In lassogrp: Lasso Regression Including Group Lasso and Adaptive Lasso

Description

Generate generalized linear model objects to be used for the (group) lasso algorithm, lasso().

Usage

lassoModel(invlink, link, nloglik, ngradient, nhessian, check,
           name = "user-specified", comment = "user-specified")
LogReg()
LinReg()
PoissReg()

Arguments

invlink	a function with argument eta implementing the inverse link function.
link	a function with argument mu implementing the link function.
nloglik	a function with arguments y, mu and weights implementing the negative log-likelihood function.
ngradient	a function with arguments x, y, mu and weights implementing the negative gradient of the log-likelihood function.
nhessian	a function with arguments x, mu and weights implementing the negative hessian of the log-likelihood function.
check	a function with argument y to check whether the response has the correct format.
name	a character name
comment	a character comment

Value

An object of class lassoModel.

Examples

LogReg()  # Logistic
PoissReg()# Poisson regression

str(LogReg())

lassogrp documentation built on July 25, 2021, 3 a.m.