qGaussian: Tools to Explore Applications of Tsallis Statistics

TL;DR

This paper introduces tools for exploring q-Gaussian distributions, including a random number generator and methods for computing key functions, aiding the analysis of systems within the nonextensive framework.

Contribution

The paper provides a comprehensive toolkit for q-Gaussian distributions, facilitating their application in various scientific fields and supporting nonextensive statistical analysis.

Findings

Implemented a q-Gaussian random number generator

Developed methods for computing probability and cumulative functions

Provided techniques for tail weight measurement using robust statistics

Abstract

q-Gaussian distribution appear in many science areas where we can find systems that could be described within a nonextensive framework. Usually, a way to assert that these systems belongs to nonextensive framework is by means of numerical data analysis. To this end, we implement random number generator for q-Gaussian distribution, while we present how to computing its probability density function, cumulative density function and quantile function besides a tail weight measurement using robust statistics.