Package: ebci 1.0.0.9000

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 (2022) <doi:10.3982/ECTA18597>.

Authors:Michal Kolesár [aut, cre], Tim Armstrong [ctb], Mikkel Plagborg-Møller [ctb]

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ebci.pdf |ebci.html
ebci/json (API)
NEWS

# Install 'ebci' in R:
install.packages('ebci', repos = c('https://kolesarm.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kolesarm/ebci/issues

Datasets:
  • cz - Neighborhood effects data from Chetty and Hendren

On CRAN:

Conda:

4.70 score 10 stars 3 scripts 116 downloads 2 exports 0 dependencies

Last updated 7 months agofrom:e0e2c763a9. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 17 2025
R-4.5-winOKMar 17 2025
R-4.5-macOKMar 17 2025
R-4.5-linuxOKMar 17 2025
R-4.4-winOKMar 17 2025
R-4.4-macOKMar 17 2025
R-4.4-linuxOKMar 17 2025
R-4.3-winOKMar 17 2025
R-4.3-macOKMar 17 2025

Exports:cvaebci

Dependencies:

Robust Empirical Bayes Confidence Intervals

Rendered fromebci.Rmdusingknitr::rmarkdownon Mar 17 2025.

Last update: 2023-11-17
Started: 2020-04-08