Package: PPSFS 0.1.2

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 (2022, <doi:10.4310/21-SII706>).

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

PPSFS_0.1.2.tar.gz
PPSFS_0.1.2.zip(r-4.7-x86_64)PPSFS_0.1.2.zip(r-4.7-arm64)PPSFS_0.1.2.zip(r-4.6-x86_64)PPSFS_0.1.2.zip(r-4.6-arm64)PPSFS_0.1.2.zip(r-4.5-x86_64)
PPSFS_0.1.2.tgz(r-4.6-x86_64)PPSFS_0.1.2.tgz(r-4.6-arm64)PPSFS_0.1.2.tgz(r-4.5-x86_64)PPSFS_0.1.2.tgz(r-4.5-arm64)
PPSFS_0.1.2.tar.gz(r-4.7-arm64)PPSFS_0.1.2.tar.gz(r-4.7-x86_64)PPSFS_0.1.2.tar.gz(r-4.6-arm64)PPSFS_0.1.2.tar.gz(r-4.6-x86_64)
PPSFS_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
PPSFS/json (API)

# 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 361 downloads 3 exports 11 dependencies

Last updated from:8303394c47. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK140
linux-devel-x86_64OK108
source / vignettesOK196
linux-release-arm64OK142
linux-release-x86_64OK110
macos-release-arm64OK109
macos-release-x86_64OK174
macos-oldrel-arm64OK109
macos-oldrel-x86_64OK166
windows-devel-arm64OK196
windows-devel-x86_64OK150
windows-release-arm64OK255
windows-release-x86_64OK109
windows-oldrel-x86_64OK100
wasm-releaseOK89

Exports:ppsfsppsfs.fitppsfsi

Dependencies:brglm2enrichwithlatticeMASSMatrixnleqslvnnetnumDerivRcppRcppArmadillostatmod