PPSFS: Partial Profile Score Feature Selection in High-Dimensional Generalized Linear Interaction Models

This is an implementation of the partial profile score feature selection (PPSFS) approach to generalized linear (interaction) models. The PPSFS is highly scalable even for ultra-high-dimensional feature space. See the paper by Xu, Luo and Chen (2021, <doi:10.4310/21-SII706>).

Version: 0.1.0
Imports: Rcpp, brglm2
LinkingTo: Rcpp, RcppArmadillo
Published: 2022-03-21
DOI: 10.32614/CRAN.package.PPSFS
Author: Zengchao Xu [aut, cre], Shan Luo [aut], Zehua Chen [aut]
Maintainer: Zengchao Xu <zengc.xu at aliyun.com>
BugReports: https://github.com/paradoxical-rhapsody/PPSFS/issues
License: GPL-3
URL: https://github.com/paradoxical-rhapsody/PPSFS
NeedsCompilation: yes
Language: en-US
Materials: README NEWS
CRAN checks: PPSFS results


Reference manual: PPSFS.pdf


Package source: PPSFS_0.1.0.tar.gz
Windows binaries: r-devel: PPSFS_0.1.0.zip, r-release: PPSFS_0.1.0.zip, r-oldrel: PPSFS_0.1.0.zip
macOS binaries: r-release (arm64): PPSFS_0.1.0.tgz, r-oldrel (arm64): PPSFS_0.1.0.tgz, r-release (x86_64): PPSFS_0.1.0.tgz, r-oldrel (x86_64): PPSFS_0.1.0.tgz


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