Package: l0ara
Type: Package
Title: Sparse Generalized Linear Model with L0 Approximation for
        Feature Selection
Version: 0.1.6
Date: 2020-02-03
Author: Wenchuan Guo, Shujie Ma, Zhenqiu Liu
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 (>= 0.12.6)
LinkingTo: Rcpp, RcppArmadillo
LazyData: TRUE
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2020-02-06 01:44:57 UTC; wguo
Repository: CRAN
Date/Publication: 2020-02-06 05:40:02 UTC
Built: R 4.2.3; x86_64-w64-mingw32; 2024-04-24 01:15:14 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
