ebci: Robust Empirical Bayes Confidence Intervals

Computes empirical Bayes confidence estimators and confidence intervals in a normal means model. The intervals are robust in the sense that they achieve correct coverage regardless of the distribution of the means. If the means are treated as fixed, the intervals have an average coverage guarantee. The implementation is based on Armstrong, Kolesár and Plagborg-Møller (2020) <arXiv:2004.03448>.

Version: 1.0.0
Depends: R (≥ 4.1.0)
Suggests: spelling, testthat (≥ 2.1.0), lpSolve, knitr, rmarkdown
Published: 2021-09-06
Author: Michal Kolesár ORCID iD [aut, cre], Tim Armstrong [ctb], Mikkel Plagborg-Møller [ctb]
Maintainer: Michal Kolesár <kolesarmi at googlemail.com>
BugReports: https://github.com/kolesarm/ebci/issues
License: MIT + file LICENSE
URL: https://github.com/kolesarm/ebci
NeedsCompilation: no
Language: en-US
Materials: NEWS
CRAN checks: ebci results

Documentation:

Reference manual: ebci.pdf
Vignettes: ebci

Downloads:

Package source: ebci_1.0.0.tar.gz
Windows binaries: r-devel: ebci_1.0.0.zip, r-release: ebci_1.0.0.zip, r-oldrel: not available
macOS binaries: r-release (arm64): ebci_1.0.0.tgz, r-release (x86_64): ebci_1.0.0.tgz, r-oldrel: not available

Linking:

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