@addmaple/stats

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Introduction ​

@addmaple/stats is a high-performance statistics library built with Rust and WebAssembly, designed to be a modern, fast alternative to jStat.

Why @addmaple/stats? ​

  • Performance: SIMD-optimized Rust code compiled to WebAssembly delivers exceptional speed
  • Modern API: Clean, functional API with TypeScript support
  • Tree-Shakeable: Import only what you need, reducing bundle size
  • Browser Compatible: Works seamlessly in both browser and Node.js environments

Architecture ​

The library is built with a clean separation of concerns:

  • Pure Rust core (stat-core) - No WebAssembly-specific code
  • Thin WASM boundary (stat-wasm) - Minimal wasm-bindgen glue
  • Ergonomic JS/TS API (js/package) - Modern, tree-shakeable API

Quick Example ​

js
import { init, mean, variance, stdev } from '@addmaple/stats';

// Initialize WASM module (required once)
await init();

// Use statistics functions
const data = [1, 2, 3, 4, 5];
const m = mean(data);        // 3
const v = variance(data);    // 2
const s = stdev(data);       // 1.414...

What's Included ​

✅ Vector Statistics ​

  • Basic operations: sum, mean, min, max, product, range
  • Variance & standard deviation: variance, sampleVariance, stdev, sampleStdev, coeffvar
  • Advanced statistics: median, mode, geomean, skewness, kurtosis
  • Quantiles: percentile, percentiles, percentileOfScore, quartiles, iqr, quantiles
  • Transformations: cumsum, cumprod, diff, rank, histogram

✅ Distributions ​

  • Normal, Gamma, Beta, Student's t, Chi-squared, Fisher F, Exponential, Poisson, Binomial, Uniform, Cauchy, Laplace, Log-normal, Weibull, Pareto, Triangular, Inverse Gamma, Negative Binomial
  • Each distribution supports: pdf, cdf, inv (inverse CDF)
  • Scalar and array operations

✅ Correlation & Covariance ​

  • covariance - Covariance between two arrays
  • corrcoeff - Pearson correlation coefficient
  • spearmancoeff - Spearman rank correlation

✅ Statistical Tests ​

  • anovaFScore / anovaTest - One-way ANOVA
  • chiSquareTest - Chi-square test
  • ttest - T-test
  • ztest - Z-test
  • regress - Linear regression
  • normalci / tci - Confidence intervals

Performance ​

See Performance Guide for detailed benchmarks comparing @addmaple/stats to jStat.