PoSI: Valid Post-Selection Inference for Linear LS Regression

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.

Version: 1.1
Suggests: MASS
Published: 2020-11-18
Author: Andreas Buja [aut], Kai Zhang [aut], Wan Zhang [cre]
Maintainer: Wan Zhang <wanz63 at live.unc.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: PoSI results

Documentation:

Reference manual: PoSI.pdf

Downloads:

Package source: PoSI_1.1.tar.gz
Windows binaries: r-devel: PoSI_1.1.zip, r-release: PoSI_1.1.zip, r-oldrel: PoSI_1.1.zip
macOS binaries: r-release (arm64): PoSI_1.1.tgz, r-oldrel (arm64): PoSI_1.1.tgz, r-release (x86_64): PoSI_1.1.tgz, r-oldrel (x86_64): PoSI_1.1.tgz
Old sources: PoSI archive

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