Exact Post Selection Inference with Applications to the Lasso
Overview
Implements the conditional estimation procedure of Lee, Sun, Sun and Taylor (2016) doi:10.1214/15-AOS1371. This procedure allows hypothesis testing on the mean of a normal random vector subject to linear constraints. Also supports computation of the MLE of the mean subject to the same constraints.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-13
- NOTE11 OK, 2 NOTE2026-05-11
- WARNING11 OK, 1 NOTE, 1 WARNING2026-05-10
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- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 9includes a package overview page
- Examples that run
- 100%3 run in a plain check
- Exported functions with examples
- 43%
- Documented parameters
- 90%
- Return-value docs
- 100%
- Help pages citing references
- 89%
Downloads
Repository
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Dependencies
Installing epsiwal adds no packages beyond those that come with R.
Code & Tests
People & History
Pick two releases to compare their code metrics.
- 0.2.0Latest2026-06-10 · current release · diff ↗ ·
added 4 exports
ci_connorm_max, mle_connorm, mle_connorm_max, pconnorm_max - RR 4.6.0 released · 2026-04-24
- 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
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 0.1.02019-07-02
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2019-07-02
- Total releases
- 2 / 7 yrs
- License
- LGPL-3 OSI
- Minimum R
- ≥ 3.0.2
- Download size
- 80 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("epsiwal")The package provides a citation file that builds its entry when R runs it. Run citation() to see it.
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