DESCRIPTION

Package: l0ara
Type: Package
Title: Sparse Generalized Linear Model with L0 Approximation for Feature
    Selection
Version: 0.1.6
Date: 2022-08-17
Author: Wenchuan Guo, Shujie Ma, Zhenqiu Liu, Tom Wenseleers
Maintainer: Wenchuan Guo <wguo007@ucr.edu>
Description: An efficient procedure for feature selection for generalized linear models with L0 penalty, including linear, logistic, Poisson, gamma, inverse Gaussian regression. Adaptive ridge algorithms are used to fit the models.
License: GPL-2
Imports: Rcpp (>= 0.12.16)
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
LazyData: TRUE
RoxygenNote: 7.0.2
NeedsCompilation: yes
Encoding: UTF-8