PoSI
1.1Valid Post-Selection Inference for Linear LS Regression
Overview
In linear LS regression, calculate for a given design matrix the multiplier K of coefficient standard errors such that the confidence intervals [b - K*SE(b), b + K*SE(b)] have a guaranteed coverage probability for all coefficient estimates b in any submodels after performing arbitrary model selection.
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- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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2 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
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.1Latest2020-11-18 · current release
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- 1.02017-01-15
Package metadata
- First published
- 2017-01-15
- Total releases
- 2 / 9 yrs
- License
- GPL-3 OSI
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