Package: glmmLasso
Type: Package
Title: Variable Selection for Generalized Linear Mixed Models by
        L1-Penalized Estimation
Version: 1.6.4
Date: 2026-01-26
Authors@R: person(given = "Andreas",
                      family = "Groll",
                      role = c("aut", "cre", "cph"),
                      email = "groll@statistik.tu-dortmund.de")
Description: A variable selection approach for generalized linear mixed models by L1-penalized estimation is provided, 
	see Groll and Tutz (2014) <doi:10.1007/s11222-012-9359-z>.
	See also Groll and Tutz (2017) <doi:10.1007/s10985-016-9359-y> for discrete survival models including heterogeneity.
Imports: stats, minqa, Matrix, Rcpp (>= 0.12.12), methods
LinkingTo: Rcpp, RcppEigen
Suggests: MASS, nlme
License: GPL-2
NeedsCompilation: yes
Packaged: 2026-01-26 17:19:35 UTC; ligges
Author: Andreas Groll [aut, cre, cph]
Maintainer: Andreas Groll <groll@statistik.tu-dortmund.de>
Repository: CRAN
Date/Publication: 2026-01-27 13:40:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-25 14:01:04 UTC; unix
Archs: glmmLasso.so.dSYM
