Package: PPSFS 0.1.0

Zengchao Xu

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>).

Authors:Zengchao Xu [aut, cre], Shan Luo [aut], Zehua Chen [aut]

PPSFS_0.1.0.tar.gz
PPSFS_0.1.0.zip(r-4.5)PPSFS_0.1.0.zip(r-4.4)PPSFS_0.1.0.zip(r-4.3)
PPSFS_0.1.0.tgz(r-4.5-x86_64)PPSFS_0.1.0.tgz(r-4.5-arm64)PPSFS_0.1.0.tgz(r-4.4-x86_64)PPSFS_0.1.0.tgz(r-4.4-arm64)PPSFS_0.1.0.tgz(r-4.3-x86_64)PPSFS_0.1.0.tgz(r-4.3-arm64)
PPSFS_0.1.0.tar.gz(r-4.5-noble)PPSFS_0.1.0.tar.gz(r-4.4-noble)
PPSFS_0.1.0.tgz(r-4.4-emscripten)PPSFS_0.1.0.tgz(r-4.3-emscripten)
PPSFS.pdf |PPSFS.html
PPSFS/json (API)
NEWS

# Install 'PPSFS' in R:
install.packages('PPSFS', repos = c('https://paradoxical-rhapsody.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/paradoxical-rhapsody/ppsfs/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

2.70 score 1 stars 153 downloads 2 exports 9 dependencies

Last updated 3 years agofrom:25ecc372b8. Checks:1 OK, 10 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 20 2025
R-4.5-win-x86_64NOTEFeb 20 2025
R-4.5-mac-x86_64NOTEFeb 20 2025
R-4.5-mac-aarch64NOTEFeb 20 2025
R-4.5-linux-x86_64NOTEFeb 20 2025
R-4.4-win-x86_64NOTEFeb 20 2025
R-4.4-mac-x86_64NOTEFeb 20 2025
R-4.4-mac-aarch64NOTEFeb 20 2025
R-4.3-win-x86_64NOTEFeb 20 2025
R-4.3-mac-x86_64NOTEFeb 20 2025
R-4.3-mac-aarch64NOTEFeb 20 2025

Exports:ppsfsppsfsi

Dependencies:brglm2enrichwithlatticeMASSMatrixnnetnumDerivRcppRcppArmadillo