R Observatory: Metrics for fastrerandomize version 0.3

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

fastrerandomize

0.3Package record

Hardware-Accelerated Rerandomization for Improved Balance

0packages depend

2.4Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Connor JerzakCRAN page ↗GitHub ↗Issues ↗

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.

Changes in 0.3

New Features

Added diagnose_rerandomization() function for pre-analysis evaluation of rerandomization designs. This function helps researchers determine optimal acceptance thresholds by computing:
Expected number of acceptable randomizations
Minimum balance criterion values
Power analysis for different threshold choices
Added fast_distance() function for hardware-accelerated pairwise distance computation supporting multiple metrics: Euclidean, Manhattan, Mahalanobis, cosine, and correlation-based distances.
Added S3 methods (print, summary, plot) for fastrerandomize_diagnostic class to visualize and summarize diagnostic results.

Show all changes in 0.3Hide the rest of the changes in 0.3

Improvements

Updated JAX backend to support CUDA 12 and CUDA 13.
Improved documentation throughout the package.
Various bug fixes and performance improvements.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("fastrerandomize", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("cjerzak/fastrerandomize-software")

Development version from cjerzak/fastrerandomize-software. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-fastrerandomize

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-fastrerandomize

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-fastrerandomize

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 3.1 min · r-oldrel-macos-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.3

READMENoVignettesYes · 1 · dynamicNEWSYes · 100% structured · mentions 0.3Citation fileYes · software entry onlyWebsitenot declared in DESCRIPTION

Help pages: 25
Examples that run: 22%2 run in a plain check · 7 never run
Exported functions with examples: 53%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 4%

Vignettes (1)

FastRerandomize Package Tutorial HTML

How these are measured

Downloads

2.4K

CRAN downloads in the past year

Rank #18,026 · ~7/day · ~198/mo

Releases R versions

Daily download trend is not available in this view yet.

28430 days

72290 days

2.4K1 year

Compare downloads with other packages →

Also on104 r2u4 autocran

How downloads are counted

Repository

cjerzak/fastrerandomize-software ↗Account: cjerzak

8Stars

1Forks

9Open issues

0Open PRs

0Releases

374Commits

17Commit identities

hardware-accelerationaccelerated-computingdistance-measuresrerandomizationapple-siliconcausal-inferencecovariate-balancecuda

374 commits · Last activity 2026-10-22 · 0% stars, 30d

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: 29
Median days to close, 50 most recently updated closed PRs: 0

Stars over time

2025-01-30 · 82026-07-07 · 8

How these are measured

PracticesBeta

Checks run against github.com/cjerzak/fastrerandomize-software on 2026-10-22.

No development-tooling practices detected in the upstream repository.

How this is detected·Detection ruleset v4 (2026-10-20)

AI coding toolsBeta

This repository shows signs of AI coding tools.

Codexfirst seen 2025-06-02
Pull request it wrote: opened by a project member
Claude Codefirst seen 2025-12-09
Named in .gitignore: CLAUDE.md
Commits: at least 5 crediting it in the message

Models named in its commits

Claude Opus 5.55 commits · Oct 2026

Counts are commits, not lines of code. Commits by a tool's accounts count once across all of its accounts. Commits crediting it are the largest count among its credit lines, a minimum.How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies

4 external dependencies (excludes base and recommended)

Installing fastrerandomize adds 11 packages (7 with compiled code, 5.5 MB of source tarballs). Heaviest: Rcpp 1.8 MB, reticulate 1.6 MB, jsonlite 1.0 MB.

Depends (1)

R >= 3.5.0

Imports (5)

reticulate assertthatutilsstatsgraphics

LinkingTo (0)

none

Suggests (2)

knitr rmarkdown

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (4)

Connor Jerzak

Author, Maintainer since 0.1 (2025)

Rebecca Goldstein

Author

Aniket Sachin Kamat

Author

Fucheng Warren Zhu

Author

Releases (3)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
0.3Latest
record
2025-12-22 · current release · diff ↗ ·
added 8 exports
compute_diff_at_tau_for_oneW_R, diagnose_rerandomization, diff_in_means_R, fast_distance, find_fiducial_interval_R, generate_randomizations_R, hotellingT2_R, randomization_test_R
R
R 4.5.0 released · 2025-04-11
0.2
record
2025-01-14 · diff ↗
0.1
record
2025-01-13
R
R 4.4.0 released · 2024-04-24

Package metadata

First published: 2025-01-13
Total releases: 3 / 1 yrs
License: GPL-3 OSI
Minimum R: ≥ 3.5.0
Bundled data: 1.8 MB / 3 files
Download size: 1.9 MB

Cite

Cite this package

Run in R for the authors' entry:

citation("fastrerandomize")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.32614/cran.package.fastrerandomize.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for fastrerandomize version 0.3 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →