grpl.model: Group Lasso Models

In grplasso: Fitting User-Specified Models with Group Lasso Penalty

Description

Generates models to be used for the group lasso algorithm.

Usage

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

Arguments

invlink	a function with arguments eta implementing the inverse link function.
link	a function with arguments 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 grpl.model.

Examples

    LogReg()

Example output

Model: Logistic Regression Model 
Comment: Binary response y has to be encoded as 0 and 1 

grplasso documentation built on July 8, 2020, 6:46 p.m.