Package: PUlasso
Type: Package
Title: High-Dimensional Variable Selection with Presence-Only Data
Version: 3.2.3
Date: 2019-4-25
Authors@R: c(person("Hyebin", "Song", role = c("aut", "cre"),
                     email = "hsong56@wisc.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: 6.1.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
URL: https://arxiv.org/abs/1711.08129
BugReports: https://github.com/hsong1/PUlasso/issues
NeedsCompilation: yes
Packaged: 2019-04-28 00:37:27 UTC; Hyebin
Author: Hyebin Song [aut, cre],
  Garvesh Raskutti [aut]
Maintainer: Hyebin Song <hsong56@wisc.edu>
Repository: CRAN
Date/Publication: 2019-04-28 07:00:03 UTC
Built: R 3.5.3; x86_64-w64-mingw32; 2020-04-22 08:07:47 UTC; windows
Archs: i386, x64
