0.0.1 • Published 1 year ago

@omdr/statistical-ml-ready v0.0.1

Weekly downloads
-
License
MIT
Repository
-
Last release
1 year ago

@omdr/statistical-ml-ready

A collection of advanced statistical and machine learning-ready tools tailored for financial data analysis, regime detection, and predictive modeling.

Installation

npm install @omdr/statistical-ml-ready

or

pnpm add @omdr/statistical-ml-ready

Features

Includes 20 tools for time-series analysis, volatility modeling, statistical profiling, and ML regime detection:

  • Z-Score (Price)
  • Hurst Exponent
  • Shannon Entropy
  • Kalman Filter
  • ARIMA Forecast
  • Linear Regression Channel
  • Standard Deviation Bands
  • Skewness / Kurtosis
  • Dickey-Fuller Test
  • Half-Life of Mean Reversion
  • Hidden Markov Models
  • K-Means Clustering (Regimes)
  • Random Walk Probability
  • Fractal Dimension
  • Wavelet Transforms
  • Correlation Heatmaps
  • PCA (Price/Volume)
  • LSTM Volatility Prediction
  • Bayesian Structural Time Series
  • Monte Carlo Simulations

Usage

// index.js
const statistical = require('@omdr/statistical-ml-ready');

// Example usage
const prices = [ 100, 101, 99, 98, 102, 105 ];
const zScore = statistical.zScore(prices);
console.log('Z-Score:', zScore);

const hurst = statistical.hurstExponent(prices);
console.log('Hurst Exponent:', hurst);

Output Examples

Z-Score: 1.23
Hurst Exponent: 0.42

Structure

.
├── src
│   ├── dev files (not included in package)
├── dist
│   ├── index.js (code is obfuscated already)
│   └── index.obf.js
├── package.json
└── README.md

Designed For

  • Node.js scripts
  • Web apps (React, Angular, Vue, etc.)
  • VS Code extensions
  • Trading dashboards
  • Custom strategy engines

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License

MIT — Free to use and extend, commercial or personal.