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Empirical Bayes ranking applicable to parallel-estimation settings where the estimated parameters are asymptotically unbiased and normal, with known standard errors. A mixture normal prior for each parameter is estimated using Empirical Bayes methods, subsequentially ranks for each parameter are simulated from the resulting joint posterior over all parameters (The marginal posterior densities for each parameter are assumed independent). Finally, experiments are ordered by expected posterior rank, although computations minimizing other plausible rank-loss functions are also given.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.2.4) |
| Published: | 2017-01-12 |
| DOI: | 10.32614/CRAN.package.EBrank |
| Author: | John Ferguson [aut, cre] |
| Maintainer: | John Ferguson <john.ferguson at nuigalway.ie> |
| License: | CC0 |
| NeedsCompilation: | no |
| CRAN checks: | EBrank results |
| Reference manual: | EBrank.pdf |
| Package source: | EBrank_1.0.0.tar.gz |
| Windows binaries: | r-devel: EBrank_1.0.0.zip, r-release: EBrank_1.0.0.zip, r-oldrel: EBrank_1.0.0.zip |
| macOS binaries: | r-release (arm64): EBrank_1.0.0.tgz, r-oldrel (arm64): EBrank_1.0.0.tgz, r-release (x86_64): EBrank_1.0.0.tgz, r-oldrel (x86_64): EBrank_1.0.0.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.