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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.2 |
rolling linux/jammy R-4.5 | PosiR_0.1.2.tar.gz |
130.0 KiB |
0.1.2 |
rolling linux/noble R-4.5 | PosiR_0.1.2.tar.gz |
129.8 KiB |
0.1.2 |
rolling source/ R- | PosiR_0.1.2.tar.gz |
98.7 KiB |
0.1.2 |
latest linux/jammy R-4.5 | PosiR_0.1.2.tar.gz |
130.0 KiB |
0.1.2 |
latest linux/noble R-4.5 | PosiR_0.1.2.tar.gz |
129.8 KiB |
0.1.2 |
latest source/ R- | PosiR_0.1.2.tar.gz |
98.7 KiB |
0.1.2 |
2026-04-26 source/ R- | PosiR_0.1.2.tar.gz |
98.7 KiB |
0.1.2 |
2026-04-23 source/ R- | PosiR_0.1.2.tar.gz |
98.7 KiB |
0.1.2 |
2026-04-09 windows/windows R-4.5 | PosiR_0.1.2.zip |
132.4 KiB |