infomeasure

This release introduces version 0.5.0 of infomeasure, featuring a comprehensive documentation overhaul, enhanced statistical testing capabilities, and 10+ new entropy estimators.

Breaking Changes

• Statistical Testing API Overhaul: Replaced p_value() and t_score() methods with comprehensive statistical_test() method returning rich StatisticalTestResult objects
• Configuration Updates: Renamed p_value_method to statistical_test_method and added statistical_test_n_tests parameter

Key Highlights

Enhanced Statistical Testing Framework

• New StatisticalTestResult Class: Rich result objects with p-values, t-scores, confidence intervals, and metadata
• Flexible Analysis: On-demand percentile calculation and statistical analysis
• Improved API: Simplified interface with structured return types

New Entropy Estimators

Added comprehensive suite of discrete entropy estimators based on meta-analysis research:

• Miller-Madow Suite: Bias-corrected estimators for H, MI, CMI, TE, CTE, KLD, and JSD
• Bayesian Entropy: Multiple prior choices (Jeffrey, Laplace, Schurmann-Grassberger, Minimax)
• Chao-Shen, Shrinkage, Grassberger Entropy: Specialized bias correction techniques
• NSB & ANSB Entropy: Bayesian estimates for undersampled data
• Zhang & Bonachela Entropy: Optimized for small datasets

Documentation Improvements

• New Estimator Selection Guide: Interactive Q&A approach for choosing optimal estimators
• New Statistical Tests Guide: Complete framework for hypothesis testing
• Enhanced Existing Guides: Major expansions with performance visualizations and research-based recommendations

Installation

You can install or upgrade the package using:

pip install infomeasure --upgrade

Documentation

For complete details and usage examples, visit the documentation.

New Guides:

• Estimator Selection Guide - Interactive approach to choosing the right estimator
• Statistical Tests Guide - Comprehensive statistical testing framework

Changelog: Full changelog

This release aims to provide a more comprehensive and research-backed toolkit for information-theoretic analysis with improved documentation and user experience.

All Commits: https://github.com/cbueth/infomeasure/compare/0.4.0...0.5.0