Package: PUlasso
Type: Package
Title: High-Dimensional Variable Selection with Presence-Only Data
Version: 3.2.5
Date: 2023-12-18
Authors@R: c(person("Hyebin", "Song", role = c("aut", "cre"),
                     email = "hps5320@psu.edu"),
            person("Garvesh", "Raskutti", role="aut",email="raskutti@stat.wisc.edu"))
Description: Efficient algorithm for solving PU (Positive and Unlabeled) problem in low or high dimensional setting with lasso or group lasso penalty. The algorithm uses Maximization-Minorization and (block) coordinate descent. Sparse calculation and parallel computing are supported for the computational speed-up. See Hyebin Song, Garvesh Raskutti (2018) <arXiv:1711.08129>.
License: GPL-2
Imports: Rcpp (>= 0.12.8), methods, Matrix, doParallel, foreach,
        ggplot2
Depends: R(>= 2.10)
LinkingTo: Rcpp, RcppEigen, Matrix
RoxygenNote: 7.2.3
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
URL: https://arxiv.org/abs/1711.08129
BugReports: https://github.com/hsong1/PUlasso/issues
NeedsCompilation: yes
Packaged: 2023-12-18 00:38:18 UTC; hyebins
Author: Hyebin Song [aut, cre],
  Garvesh Raskutti [aut]
Maintainer: Hyebin Song <hps5320@psu.edu>
Repository: CRAN
Date/Publication: 2023-12-18 14:40:06 UTC
Built: R 4.2.3; aarch64-apple-darwin20; 2023-12-18 17:21:46 UTC; unix
Archs: PUlasso.so.dSYM
