SPSP
0.2.0Selection by Partitioning the Solution Paths
Overview
An implementation of the feature Selection procedure by Partitioning the entire Solution Paths (namely SPSP) to identify the relevant features rather than using a single tuning parameter. By utilizing the entire solution paths, this procedure can obtain better selection accuracy than the commonly used approach of selecting only one tuning parameter based on existing criteria, cross-validation (CV), generalized CV, AIC, BIC, and extended BIC (Liu, Y., & Wang, P. (2018) doi:10.1214/18-EJS1434). It is more stable and accurate (low false positive and false negative rates) than other variable selection approaches. In addition, it can be flexibly coupled with the solution paths of Lasso, adaptive Lasso, ridge regression, and other penalized estimators.
Install
Health
- OK2026-04-2214 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1813 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 20%
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Checks run against github.com/xiaoruizhu/spsp on 2026-07-30.
Dependencies
Nothing depends on this yet.
Code & Tests
Datasets
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 0.2.0Latest
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 0.1.12022-02-22 · diff ↗
- 0.1.02021-08-02
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2021-08-02
- Total releases
- 3 / 5 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 740 KB / 1 file
- Download size
- 756 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet