# jstat/jstat

JavaScript Statistical Library

Repository: https://github.com/jstat/jstat
Canonical: https://ross.abutalabs.com/products/jstat
Homepage: http://jstat.github.io/
Language: JavaScript
License: MIT
License Family: permissive
Last push: 2026-02-28T08:23:25+00:00

## Health v2 (maintenance only)
Score: 63/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 69, release rhythm 35, longevity 100
- inputs: {"age_days": 5641, "days_push": 186, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1806, forks 248 (observed 2026-08-28T04:05:39.065224+00:00)

## What it is
jStat is a JavaScript library providing native implementations of statistical functions, including many probability distributions (weibull, cauchy, poisson, hypergeometric, beta) with pdf, cdf, inverse, mean, variance, and sampling. It also offers linear algebra, statistical tests, and regression models, and works in both the browser and Node.js.

## Use cases
- compute probability distribution pdf and cdf values in JavaScript
- calculate statistical tests like t-test in the browser
- run linear regression on a dataset in Node.js
- sample random values from a beta or poisson distribution
- compute mean, variance, and standard deviation of a dataset
- find inverse cdf / critical values for distributions

## When to choose
- you need a broad set of statistical distributions and tests in JavaScript
- you want a lightweight, dependency-free stats library usable in the browser via CDN
- you need regression or linear algebra helpers alongside distribution functions

## When to avoid
- you need high-performance numerical computing for large datasets (use Python/R instead)
- you need machine learning features beyond classical statistics
- you need TypeScript typings or modern ESM-first packaging

## Facets
- artifact type: library
- maturity: stable
- function: math, data-science
- domain: data-science, web-development
- platform: browser
- tags: statistics, probability-distributions, regression, linear-algebra, nodejs, javascript

## Member repositories
- jstat/jstat (main) score 63

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:39.065224+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:21:30.098384+00:00, confidence not recorded.
  - readme: https://github.com/jstat/jstat (fetched 2026-08-28T04:05:39.065224+00:00, sha 811b53f88727)
  - homepage: http://jstat.github.io/ (fetched 2026-08-29T11:00:39.013751+00:00, sha 76b5678d5063)
  - registry_npm: https://registry.npmjs.org/jstat (fetched 2026-08-29T11:00:39.016981+00:00, sha 6c293101e3b1)
- Data as of 2026-08-30T08:39:29.467469+00:00.