This package implements both the discrete and continuous maximum likelihood estimators for fitting the power-law distribution to data. Additionally, a goodness-of-fit based approach is used to estimate the lower cutoff for the scaling region.

analyzing power-laws fits of financial time series data

Shows the Bitcoin & Kaspa power law price channels

Prediction with Pretrained autoencoders

This repository contains FDP'18 presentations and R scripts.

Simulation of Rayleigh Benard Convection of a powerlaw fluid in rectangular and cylindrical cavities using rheoTool

Curve fitting routines for astrophysical (SDSS) spectrographs

Star Data Base

R package for convolution of Pareto distributions

This is a sample implementation of "Power-law Distribution Aware Trust Prediction", IJCAI 2018.

Python wrapper for the Powerlaw Collision Avoidance model

Estimate tail parameters of heavy-tailed distributions (including power law exponent gamma) in Python

This project evolves around the concept of networks, centralities, and community detection, and infection simulation.

The project for the course "Web Information Retrieval"

A Rust library and command-line tool for analyzing Power-Law distributions in empirical data.

Code behind the FlightRank website and the data mining that went into it

langstats is an R package designed to help language researchers explore the statistical properties of natural language in an accessible and agile way.

Interactive BTC Minotaur investment simulator with modern React UI

Fit powerlaw distributions with a maximum-likelihood fitting procedure

Bitcoin & Kaspa Power Law Predictor 2026 📈 | Price Channel Analysis Tool