# sgl_lambda_sequence: Generic routine for computing a lambda sequence for the regularization path

### Description

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

### Usage

 1 2 3 4  sgl_lambda_sequence(module_name, PACKAGE, data, covariateGrouping, groupWeights, parameterWeights, alpha = 0.5, d = 100L, lambda.min, algorithm.config = sgl.standard.config) 

### Arguments

 call_sym reference to objective specific C++ routines PACKAGE data sampleGrouping covariateGrouping grouping of covariates, a vector of length p. Each element of the vector specifying the group of the covariate. groupWeights the group weights, a vector of length m+1 (the number of groups). parameterWeights a matrix of size K \times (p+1). 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 lambda sequence lambda.min the smallest lambda value in the computed sequence. algorithm.config the algorithm configuration to be used.

### Value

a vector of length d containing the compute lambda sequence.

### Author(s)

Martin Vincent

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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