This is a tool to find the optimal rerandomization threshold in non-sequential experiments. We offer three procedures based on assumptions made on the residuals distribution: (1) normality assumed (2) excess kurtosis assumed (3) entire distribution assumed. Illustrations are included. Also included is a routine to unbiasedly estimate Frobenius norms of variance-covariance matrices. Details of the method can be found in "Optimal Rerandomization via a Criterion that Provides Insurance Against Failed Experiments" Adam Kapelner, Abba M. Krieger, Michael Sklar and David Azriel (2020) <doi:10.48550/arXiv.1905.03337>.
| Version: | 1.1 |
| Depends: | R (≥ 3.2.0), ggplot2 (≥ 3.0), momentchi2 (≥ 0.1.5), GreedyExperimentalDesign (≥ 1.3) |
| Imports: | stats |
| Published: | 2021-01-28 |
| DOI: | 10.32614/CRAN.package.OptimalRerandExpDesigns |
| Author: | Adam Kapelner, Michael Sklar, Abba M. Krieger and David Azriel |
| Maintainer: | Adam Kapelner <kapelner at qc.cuny.edu> |
| License: | GPL-3 |
| URL: | https://github.com/kapelner/OptimalRerandExpDesigns |
| NeedsCompilation: | no |
| Citation: | OptimalRerandExpDesigns citation info |
| Materials: | ChangeLog |
| CRAN checks: | OptimalRerandExpDesigns results |
| Reference manual: | OptimalRerandExpDesigns.pdf |
| Package source: | OptimalRerandExpDesigns_1.1.tar.gz |
| Windows binaries: | r-devel: OptimalRerandExpDesigns_1.1.zip, r-release: OptimalRerandExpDesigns_1.1.zip, r-oldrel: OptimalRerandExpDesigns_1.1.zip |
| macOS binaries: | r-release (arm64): OptimalRerandExpDesigns_1.1.tgz, r-oldrel (arm64): OptimalRerandExpDesigns_1.1.tgz, r-release (x86_64): OptimalRerandExpDesigns_1.1.tgz, r-oldrel (x86_64): OptimalRerandExpDesigns_1.1.tgz |
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