Confidence Interval Post-Selection of Variable
Overview
Calculates confidence intervals after variable selection using repeated data splits. The package offers methods to address the challenges of post-selection inference, ensuring more accurate confidence intervals in models involving variable selection. The two main functions are 'lmps', which records the different models selected across multiple data splits as well as the corresponding coefficient estimates, and 'cips', which takes the lmps object as input to select variables and perform inferences using two types of voting.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 6includes a package overview page
- Examples that run
- 83%5 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
2 development-tooling and community-health practices detected across 2 families in the upstream repository
Checks run against github.com/diallo0/cipostselect on 2026-10-21.
Dependencies
Code & Tests
People & History
Package metadata
- First published
- 2024-10-02
- Total releases
- 4 / 2 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 9.3 KB
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