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PosiR: Post-Selection Inference via Simultaneous Confidence Intervals
Post-selection inference in linear regression models, constructing simultaneous confidence intervals across a user-specified universe of models. Implements the methodology described in Kuchibhotla, Kolassa, and Kuffner (2022) "Post-Selection Inference" <doi:10.1146/annurev-statistics-100421-044639> to ensure valid inference after model selection, with applications in high-dimensional settings like Lasso selection.
Package details |
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| Author | Henry Chukwuma [aut, cre] |
| Maintainer | Henry Chukwuma <chukyhenry55@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.1.2 |
| URL | https://github.com/Chukyhenry/PosiR |
| Package repository | View on CRAN |
| Installation |
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