Package: glamlasso
Type: Package
Title: Penalization in Large Scale Generalized Linear Array Models
Version: 3.0.1
Date: 2021-05-10
Author: Adam Lund
Maintainer: Adam Lund <adam.lund@math.ku.dk>
Description: Efficient design matrix free  lasso penalized estimation in large scale 2 and 3-dimensional generalized linear array model framework. The procedure is based on the gdpg algorithm from Lund et al. (2017) <doi:10.1080/10618600.2017.1279548>. Currently Lasso or Smoothly Clipped Absolute Deviation (SCAD) penalized estimation is possible for the following models: The Gaussian model with identity link, the Binomial model with logit link, the Poisson model with log link and the Gamma model with log link. It is also possible to include a  component in the model with non-tensor design e.g an intercept. Also provided are functions, glamlassoRR() and glamlassoS(), fitting special cases of GLAMs. 
License: GPL-3
Imports: Rcpp (>= 0.11.2)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-05-13 17:15:49 UTC; adam
Repository: CRAN
Date/Publication: 2021-05-16 22:30:06 UTC
Built: R 4.4.0; aarch64-apple-darwin20; 2024-04-06 00:30:37 UTC; unix
Archs: glamlasso.so.dSYM
