Package: PPSFS 0.1.3

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_0.1.3.tar.gz
PPSFS_0.1.3.tar.gz(r-4.7-arm64)PPSFS_0.1.3.tar.gz(r-4.7-x86_64)PPSFS_0.1.3.tar.gz(r-4.6-arm64)PPSFS_0.1.3.tar.gz(r-4.6-x86_64)
PPSFS_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
PPSFS/json (API)
NEWS

# Install 'PPSFS' in R:
install.packages('PPSFS', repos = c('https://cran.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

2.00 score 506 downloads 3 exports 11 dependencies

Last updated from:73dba0fea5. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK163
linux-devel-x86_64OK124
source / vignettesOK214
linux-release-arm64OK117
linux-release-x86_64OK125
wasm-releaseOK109

Exports:ppsfsppsfs.fitppsfsi

Dependencies:brglm2enrichwithlatticeMASSMatrixnleqslvnnetnumDerivRcppRcppArmadillostatmod