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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1 |
rolling linux/jammy R-4.5 | OptimalRerandExpDesigns_1.1.tar.gz |
73.4 KiB |
1.1 |
rolling linux/noble R-4.5 | OptimalRerandExpDesigns_1.1.tar.gz |
73.3 KiB |
1.1 |
rolling source/ R- | OptimalRerandExpDesigns_1.1.tar.gz |
13.3 KiB |
1.1 |
latest linux/jammy R-4.5 | OptimalRerandExpDesigns_1.1.tar.gz |
73.4 KiB |
1.1 |
latest linux/noble R-4.5 | OptimalRerandExpDesigns_1.1.tar.gz |
73.3 KiB |
1.1 |
latest source/ R- | OptimalRerandExpDesigns_1.1.tar.gz |
13.3 KiB |
1.1 |
2026-04-26 source/ R- | OptimalRerandExpDesigns_1.1.tar.gz |
13.3 KiB |
1.1 |
2026-04-23 source/ R- | OptimalRerandExpDesigns_1.1.tar.gz |
13.3 KiB |
1.1 |
2026-04-09 windows/windows R-4.5 | OptimalRerandExpDesigns_1.1.zip |
77.2 KiB |
1.1 |
2025-04-20 source/ R- | OptimalRerandExpDesigns_1.1.tar.gz |
13.3 KiB |
Dependencies (latest)
Depends
- ggplot2 (>= 3.0)
- momentchi2 (>= 0.1.5)
- GreedyExperimentalDesign (>= 1.3)