test.data

datasets

data

Fast generic solver for sparse group lasso optimization problems.
    The loss (objective) function must be defined in a C++ module. This package
    apply template metaprogramming techniques, therefore -- when compiling the
    package from source -- a high level of optimization is needed to gain full
    speed (e.g. for the GCC compiler use -O3). Use of multiple processors for
    cross validation and subsampling is supported through OpenMP. The Armadillo
    C++ library is used as the primary linear algebra engine. (The sglOptim
    package version a.b.c.d is interpreted as follows: a - primary
    version, b - major updates and fixes, c - source revision as corresponding
    to R-Forge, d - minor fixes made only to the CRAN
    branch of the source)

test.data: Simulated data set

Description

Arguments