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fastrerandomize  

Hardware-Accelerated Rerandomization for Improved Balance
View on CRAN: Click here


Download and install fastrerandomize package within the R console
Install from CRAN:
install.packages("fastrerandomize")

Install from Github:
library("remotes")
install_github("cran/fastrerandomize")

Install by package version:
library("remotes")
install_version("fastrerandomize", "0.3")



Attach the package and use:
library("fastrerandomize")
Maintained by
Connor Jerzak
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-01-13
Latest Update: 2025-01-14
Description:
Provides hardware-accelerated tools for performing rerandomization and randomization testing in experimental research. Using a 'JAX' backend, the package enables exact rerandomization inference even for large experiments with hundreds of billions of possible randomizations. Key functionalities include generating pools of acceptable rerandomizations based on covariate balance, conducting exact randomization tests, and performing pre-analysis evaluations to determine optimal rerandomization acceptance thresholds. The package supports various hardware acceleration frameworks including 'CPU', 'CUDA', and 'METAL', making it versatile across accelerated computing environments. This allows researchers to efficiently implement stringent rerandomization designs and conduct valid inference even with large sample sizes. The package is partly based on Jerzak and Goldstein (2023) <doi:10.48550/arXiv.2310.00861>.
How to cite:
Connor Jerzak (2025). fastrerandomize: Hardware-Accelerated Rerandomization for Improved Balance. R package version 0.3, https://cran.r-project.org/web/packages/fastrerandomize. Accessed 06 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:38), 0.1 (2025-01-13 19:00), 0.2 (2025-01-14 09:00)
Other packages that cited fastrerandomize R package
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Other R packages that fastrerandomize depends, imports, suggests or enhances
Complete documentation for fastrerandomize
Functions, R codes and Examples using the fastrerandomize R package
Full fastrerandomize package functions and examples
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