ebnm: Solve the Empirical Bayes Normal Means Problem (original) (raw)
Provides simple, fast, and stable functions to fit the normal means model using empirical Bayes. For available models and details, see function ebnm(). Our JSS article, Willwerscheid, Carbonetto, and Stephens (2025) <doi:10.18637/jss.v114.i03>, provides a detailed introduction to the package.
| Version: | 1.1-42 |
|---|---|
| Depends: | R (≥ 3.3.0) |
| Imports: | stats, ashr, mixsqp, truncnorm, trust, deconvolveR, magrittr, rlang, dplyr, ggplot2 |
| Suggests: | testthat, REBayes, horseshoe, knitr, rmarkdown, cowplot, mcmc, numDeriv |
| Published: | 2025-10-10 |
| DOI: | 10.32614/CRAN.package.ebnm |
| Author: | Jason Willwerscheid [aut], Matthew Stephens [aut], Peter Carbonetto [aut, cre], Andrew Goldstein [ctb], Yusha Liu [ctb] |
| Maintainer: | Peter Carbonetto <peter.carbonetto at gmail.com> |
| BugReports: | https://github.com/stephenslab/ebnm/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/stephenslab/ebnm |
| NeedsCompilation: | no |
| Citation: | ebnm citation info |
| Materials: | README |
| CRAN checks: | ebnm results |
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