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Conduct post-selection inference for regression coefficients in linear models after they have been selected by adjusted R squared. The p-values and confidence intervals are valid after model selection with the same data. This allows the user to use all data for both model selection and inference without losing control over the type I error rate. The provided tests are more powerful than data splitting, which bases inference on less data since it discards all information used for selection.
Version: | 0.0.0.1 |
Imports: | lmf, stats, utils, VGAM |
Published: | 2024-08-26 |
DOI: | 10.32614/CRAN.package.PoSIAdjRSquared |
Author: | Sarah Pirenne [aut, cre], Gerda Claeskens [aut] |
Maintainer: | Sarah Pirenne <sarah.pirenne at kuleuven.be> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | PoSIAdjRSquared results |
Reference manual: | PoSIAdjRSquared.pdf |
Package source: | PoSIAdjRSquared_0.0.0.1.tar.gz |
Windows binaries: | r-devel: PoSIAdjRSquared_0.0.0.1.zip, r-release: PoSIAdjRSquared_0.0.0.1.zip, r-oldrel: PoSIAdjRSquared_0.0.0.1.zip |
macOS binaries: | r-release (arm64): PoSIAdjRSquared_0.0.0.1.tgz, r-oldrel (arm64): PoSIAdjRSquared_0.0.0.1.tgz, r-release (x86_64): PoSIAdjRSquared_0.0.0.1.tgz, r-oldrel (x86_64): PoSIAdjRSquared_0.0.0.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.