Partial Profile Score Feature Selection in High-Dimensional Generalized Linear Interaction Models
Overview
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.
- fix the issue related to
vnu.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-04-22
- ERROR13 OK, 1 ERROR2026-04-18
- OK14 OK2026-03-10
Documentation
- Help pages
- 3 (1 internal)includes a package overview page
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 83%
- Return-value docs
- 50%
- Help pages citing references
- 67%
Downloads
Repository
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1 development-tooling and community-health practice detected across 1 family in the upstream repository
Checks run against github.com/paradoxical-rhapsody/ppsfs on 2026-10-21.
Dependencies
Installing PPSFS adds 7 packages (5 with compiled code, 5.5 MB of source tarballs). Heaviest: brglm2 2.3 MB, Rcpp 1.8 MB, RcppArmadillo 1.0 MB.
Code & Tests
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- RR 4.6.0 released · 2026-04-24
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- 0.1.12025-07-04 · diff ↗
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 0.1.02022-03-21
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2022-03-21
- Total releases
- 3 / 4 yrs
- License
- GPL-3 OSI
- Download size
- 7.9 KB
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