How to cite ChakataStat

Last updated: August 23, 2026

ChakataStat is archived on Zenodo, which gives it two kinds of DOI. Which one you want depends on what you are pointing at: the software, or the exact build that produced your numbers.

Citing the software

Use the concept DOI when you mean ChakataStat itself — in a methods section that names the tool, a bibliography entry, or a link that should keep working after the next release. It never changes, and it always resolves to the newest version with every earlier one listed beneath it.

Amani, E. (2026). ChakataStat [Computer software]. https://doi.org/10.5281/zenodo.22043444

Citing the version you ran

Use a version DOI when the result has to be reproducible — a paper reporting statistics ChakataStat computed, a pre-registration, a submitted analysis script. It pins one release and one archived record, so a reader can obtain the same build you used. ChakataStat prints its version under Help → About and at the foot of every output document.

Amani, E. (2026). ChakataStat (Version 0.21.0) [Computer software]. https://doi.org/10.5281/zenodo.22064586

Version DOIs

Releases before 0.20.0 predate the archive and have no DOI; cite those with the concept DOI and the version number. Each version record archives the release's Linux installer, its SHA256SUMS.txt checksums and the license — not the source, which is not public.

BibTeX

@software{chakatastat,
  author  = {Amani, Edward},
  title   = {ChakataStat},
  year    = {2026},
  version = {0.21.0},
  doi     = {10.5281/zenodo.22064586},
  url     = {https://doi.org/10.5281/zenodo.22064586}
}

Drop the version field and swap in 10.5281/zenodo.22043444 to cite the software rather than one release.

Citing the numbers, not just the tool

If a reviewer asks how the statistics were verified, the validation report is the citable answer: it lists every statistic pinned to an independently computed reference value, the tolerance recorded for each one, the NIST certified datasets scored by digits of agreement, and the convention chosen wherever a statistic has more than one defensible definition.