Package: PUlasso
Type: Package
Title: High-Dimensional Variable Selection with Presence-Only Data
Version: 2.1
Date: 2017-12-11
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 Unlabelled) 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 via 'OpenMP' are supported for the computational speed-up. See Hyebin Song, Garvesh Raskutti (2017) <arXiv:1711.08129>.
License: GPL-2
Imports: Rcpp (>= 0.12.8), methods
Depends: R(>= 2.10), Matrix, bigmemory
LinkingTo: Rcpp, BH, bigmemory, RcppEigen
RoxygenNote: 6.0.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
URL: https://arxiv.org/abs/1711.08129
BugReports: https://github.com/hsong1/PUlasso/issues
NeedsCompilation: yes
Packaged: 2017-12-18 02:29:26 UTC; Hyebin
Author: Hyebin Song [aut, cre],
  Garvesh Raskutti [aut]
Maintainer: Hyebin Song <hsong56@wisc.edu>
Repository: CRAN
Date/Publication: 2018-01-03 13:49:07 UTC
