sgl_lambda_sequence: Generic routine for computing a lambda sequence for the...

In SglOptimizer: Sparse group lasso optimizer

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

  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

SglOptimizer documentation built on May 2, 2019, 5:17 p.m.