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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) <doi:10.48550/arXiv.1711.08129>.
Version: | 3.2.5 |
Depends: | R (≥ 2.10) |
Imports: | Rcpp (≥ 0.12.8), methods, Matrix, doParallel, foreach, ggplot2 |
LinkingTo: | Rcpp, RcppEigen, Matrix |
Suggests: | testthat, knitr, rmarkdown |
Published: | 2023-12-18 |
DOI: | 10.32614/CRAN.package.PUlasso |
Author: | Hyebin Song [aut, cre], Garvesh Raskutti [aut] |
Maintainer: | Hyebin Song <hps5320 at psu.edu> |
BugReports: | https://github.com/hsong1/PUlasso/issues |
License: | GPL-2 |
URL: | https://arxiv.org/abs/1711.08129 |
NeedsCompilation: | yes |
Materials: | README |
CRAN checks: | PUlasso results |
Reference manual: | PUlasso.pdf |
Vignettes: |
PUlasso-vignette |
Package source: | PUlasso_3.2.5.tar.gz |
Windows binaries: | r-devel: PUlasso_3.2.5.zip, r-release: PUlasso_3.2.5.zip, r-oldrel: PUlasso_3.2.5.zip |
macOS binaries: | r-release (arm64): PUlasso_3.2.5.tgz, r-oldrel (arm64): PUlasso_3.2.5.tgz, r-release (x86_64): PUlasso_3.2.5.tgz, r-oldrel (x86_64): PUlasso_3.2.5.tgz |
Old sources: | PUlasso archive |
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These binaries (installable software) and packages are in development.
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