OptimalRerandExpDesigns: Optimal Rerandomization Experimental Designs

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) <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
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-release (x86_64): OptimalRerandExpDesigns_1.1.tgz, r-oldrel: OptimalRerandExpDesigns_1.1.tgz


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