statcore

The statistical engine behind proj-mvp.vercel.app. Eleven methods, twenty modules, zero dependencies, runs in the browser. Every number on those sixty product pages is computed by this code at build time.

20 modules · 11 methods · 0 dependencies · 90 tests · MIT

Why you can trust the numbers

The changepoint core (cusum, bocd, bh) is a port of a tested Python implementation, and it is pinned to that implementation at 1e-6 by 25 parity tests running against fixtures generated from the original. If the port drifts, the suite goes red.

The eleven methods with no reference implementation to diff against are tested a different way — against properties the mathematics guarantees rather than against an oracle:

• conformal coverage holds at every alpha, on a deliberately skewed error distribution
• James–Stein shrinkage beats raw means on total squared error, on all 50 seeds
• the always-valid interval contains the truth along the whole monitoring path, not just at the end
• the GPD fit recovers a known shape parameter from exactly-sampled Pareto tails
• capture–recapture lands within 15% of a hidden population size

That distinction matters: a test that only checks the code agrees with itself proves nothing. These check it agrees with the theorem.

Install

npm install statcore

What is in it

Module	Question it answers	Entry points
cusum, bocd, detect	Did this series change, and when?	cusum, bocd, runDetection
bh	You tested a thousand things. Which findings survive?	applyBHCorrection, bhAdjust
naive	What the threshold rule you use today would have said	naiveAlerts, compareToNaive
power, bootstrap	Could you even have seen the effect?	requiredSampleSize, minimumDetectableEffect, pairedBootstrap
sequential, ratesprt	Is it safe to look at this every morning?	mSPRT, rateSPRT
conformal	How sure are you, with a guarantee?	fitConformalRegressor, calibrateAbstention
causal	Did you cause it?	differenceInDifferences, syntheticControl
survival	When did it happen, not how many	kaplanMeier, logRank, hazardByPeriod
extremes	How bad can it get?	tailRisk
hierarchical	Is that rank real?	shrinkRates, differsFromPopulation
benford, capture	What is hidden, what did you miss?	benfordTest, captureRecapture
judge	What did the LLM judge get wrong?	correctJudgedRate, compareJudged
seasonal, stats	Weekly structure; the numeric utilities under everything	seededRandom, normPpf, quantile

Three rules the code follows

1. CUSUM runs on day-over-day percentage changes, not levels. A growing series must not alert on its own growth.
2. Multiplicity is corrected across everything tested in a run. runDetection returns the suppressed findings as well as the survivors; the suppressed list is a feature.
3. Anything that peeks is always-valid. mSPRT and rateSPRT keep their error rate under continuous monitoring, and their intervals agree with their tests by construction.

Example

import { runDetection, mSPRT, calibrateAbstention } from 'statcore'

// Which of these series changed, after correcting for testing all of them?
const run = runDetection(series, { fdr: 0.05, minConfidence: 0.9 })
run.findings    // survived Benjamini-Hochberg
run.suppressed  // would have alerted without it

// Watch a canary after every batch without inflating the false-halt rate.
const seq = mSPRT(control, treatment, { alpha: 0.05, tau: 0.03, step: 250 })
seq.stoppedAt   // first n at which the always-valid test crossed, or null

// Turn any confidence score into a threshold with a guaranteed error rate.
const policy = calibrateAbstention(scores, correct, 0.02)
policy.threshold

Build

npm install
npm test     # 90 tests, including the 25 parity tests
npm run build

MIT.