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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

Documentation:

Reference manual: PPSFS.pdf

Downloads:

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=PPSFS to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.