CRAN/E | PUlasso

PUlasso

High-Dimensional Variable Selection with Presence-Only Data

Installation

About

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.org/abs/1711.08129
Bug report File report

Key Metrics

Version 3.2.5
R ≥ 2.10
Published 2023-12-18 133 days ago
Needs compilation? yes
License GPL-2
CRAN checks PUlasso results

Downloads

Yesterday 3 -57%
Last 7 days 70 -4%
Last 30 days 249 -17%
Last 90 days 865 +1%
Last 365 days 2.344 +16%

Maintainer

Maintainer

Hyebin Song

hps5320@psu.edu

Authors

Hyebin Song

aut / cre

Garvesh Raskutti

aut

Material

README
Reference manual
Package source

Vignettes

PUlasso-vignette

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Old Sources

PUlasso archive

Depends

R ≥ 2.10

Imports

Rcpp ≥ 0.12.8
methods
Matrix
doParallel
foreach
ggplot2

Suggests

testthat
knitr
rmarkdown

LinkingTo

Rcpp
RcppEigen
Matrix