# sgl_lambda_sequence: Computing a Lambda Sequence In sglOptim: Generic Sparse Group Lasso Solver

## Description

Computes a decreasing lambda sequence of length d. The sequence ranges from a data determined maximal lambda λ_\textrm{max} to the user supplied lambda.min.

## Usage

 1 2 3 4 sgl_lambda_sequence(module_name, PACKAGE, data, parameterGrouping = NULL, groupWeights = NULL, parameterWeights = NULL, alpha, d = 100, lambda.min, algorithm.config = sgl.standard.config, lambda.min.rel = FALSE) 

## Arguments

 module_name reference to objective specific C++ routines. PACKAGE name of the calling package. data list of data objects – will be parsed to the specified module. parameterGrouping grouping of parameters, a vector of length p. Each element of the vector specifying the group of the parameters in the corresponding column of β. groupWeights group weights, a vector of length length(unique(parameterGrouping)) (the number of groups). parameterWeights parameters weights, a matrix of size q \times p. alpha the α value, 0 for group lasso, 1 for lasso, between 0 and 1 gives a sparse group lasso penalty. d the length of the lambda sequence. lambda.min the smallest lambda value in the computed sequence. algorithm.config the algorithm configuration. lambda.min.rel is lambda.min relative to lambda.max ? (i.e. actual lambda min used is lambda.min*lambda.max, with lambda.max the computed maximal lambda value)

## Value

a vector of length d containing the compute lambda sequence.

## Author(s)

Martin Vincent

sglOptim documentation built on Oct. 21, 2018, 9:04 a.m.