@danielsimonjr/mathts-statistics

Statistics & probability for MathTS — a focused, standalone library covering descriptive statistics, probability distributions, hypothesis tests, and combinatorics.

The implementations live in @danielsimonjr/mathts-functions and are re-exported here, not duplicated — this package is a curated entry point over the statistics/probability surface. Every function is externally oracle-pinned (SciPy / NumPy / mpmath / closed form) in the functions package's test suite, so the numbers are trustworthy, not just green.

Install

npm install @danielsimonjr/mathts-statistics

What's included

• Descriptive statistics — mean, median, mode, variance, std, quantileSeq, mad, iqr, sem, zscore, moment, skewness, kurtosis, gmean, hmean, cov, corr, corrcoef, rankdata, and the three correlation coefficients corr (Pearson), spearman, kendallTau (τ_b).
• Parallel-first reductions — worker-pool-accelerated parallelStat* (Mean, Variance, Std, Median, Quantile, Histogram, Corr, …) plus quickSelect/medianSelect.
• Probability distributions — 14 distribution objects with .pdf/.cdf/.quantile/.mean/.variance/.sample (normalDist, gammaDist, betaDist, binomialDist, poissonDist, exponentialDist, chiSquaredDist, fDist, tDist, logNormalDist, uniformDist, weibullDist, hypergeometricDist, negativeBinomialDist), plus free CDF/quantile functions and the entropy/jsDivergence divergences.
• Hypothesis tests — studentTTest (one/two-sample), studentTTestPaired, anova, chiSquareTest, kolmogorovSmirnovTest (one-sample) + kolmogorovSmirnov2Test (two-sample), mannWhitneyTest, shapiroWilkTest, leveneTest, bartlettTest, proportionZTest, binomialTest, fTest, jarqueBera, kruskalWallis, wilcoxon, fisherExact, tukeyHSD, principalComponentAnalysis.
• Probability & combinatorics — combinations, permutations, multinomial, factorial, doubleFactorial, risingFactorial, fallingFactorial, subfactorial, bernoulli, gamma, lgamma, kldivergence, and seedable RNG (random, randomInt, pickRandom, seedProbabilityRng).

Example

import {
  anova,
  kendallTau,
  hypergeometricDist,
  kolmogorovSmirnov2Test,
} from '@danielsimonjr/mathts-statistics';

anova([
  [8.1, 8.3, 7.9],
  [9.1, 9.5, 8.9],
]); // one-way ANOVA F + p
kendallTau([1, 2, 3, 4, 5], [2, 1, 4, 3, 5]); // 0.6
hypergeometricDist(50, 5, 10).pmf(1); // 0.4313371972
kolmogorovSmirnov2Test([1, 2, 3], [2, 3, 4]); // { statistic, pValue }

License

MIT