THAP: A Matlab Toolkit for Learning with Hawkes Processes

TL;DR

The paper introduces THAP, an open-source Matlab toolkit that implements various algorithms for learning and analyzing Hawkes processes, facilitating research and education in asynchronous event sequence analysis.

Contribution

It provides a comprehensive collection of recent and classic algorithms for Hawkes process modeling in a user-friendly Matlab toolkit.

Findings

Includes state-of-the-art algorithms for Hawkes processes

Supports analysis of complex event sequences

Enhances research and education in point process modeling

Abstract

As a powerful tool of asynchronous event sequence analysis, point processes have been studied for a long time and achieved numerous successes in different fields. Among various point process models, Hawkes process and its variants attract many researchers in statistics and computer science these years because they capture the self- and mutually-triggering patterns between different events in complicated sequences explicitly and quantitatively and are broadly applicable to many practical problems. In this paper, we describe an open-source toolkit implementing many learning algorithms and analysis tools for Hawkes process model and its variants. Our toolkit systematically summarizes recent state-of-the-art algorithms as well as most classic algorithms of Hawkes processes, which is beneficial for both academical education and research. Source code can be downloaded from https://github.com/HongtengXu/Hawkes-Process-Toolkit.