# Conjugate Bayesian Two-step Change Point Detection for Hawkes Process

Source: [Conjugate Bayesian Two-step Change Point Detection for Hawkes Process](<https://www.sota2.com/research/paper/68fa75321e209131cea66574>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-01-02T13:30:10.250Z

Authors: Zeyue Zhang, Xiaoling Lu, Feng Zhou

Published: 2024-09-26T07:16:38.000Z

## Abstract

The Bayesian two-step change point detection method is popular for the Hawkes process due to its simplicity and intuitiveness. However, the non-conjugacy between the point process likelihood and the prior requires most existing Bayesian two-step change point detection methods to rely on non-conjugate inference methods. These methods lack analytical expressions, leading to low computational efficiency and impeding timely change point detection. To address this issue, this work employs data augmentation to propose a conjugate Bayesian two-step change point detection method for the Hawkes process, which proves to be more accurate and efficient. Extensive experiments on both synthetic and real data demonstrate the superior effectiveness and efficiency of our method compared to baseline methods. Additionally, we conduct ablation studies to explore the robustness of our method concerning various hyperparameters. Our code is publicly available at https://github.com/Aurora2050/CoBay-CPD.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Change Point Detection on Synthetic Hawkes Process dataset](<https://www.sota2.com/research/sota/change-point-detection-on-synthetic-hawkes-process-dataset.md>): Change Point Detection; Synthetic Hawkes Process dataset; FNR: 13.

- [Change Point Detection on WannaCry Cyber Attack](<https://www.sota2.com/research/sota/change-point-detection-on-wannacry-cyber-attack.md>): Change Point Detection; WannaCry Cyber Attack; FNR: 21.

- [Change Point Detection on NYC Vehicle Collisions](<https://www.sota2.com/research/sota/change-point-detection-on-nyc-vehicle-collisions.md>): Change Point Detection; NYC Vehicle Collisions; FNR: 13.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2409.17591>)

[PDF](<https://arxiv.org/pdf/2409.17591.pdf>)

[Implementation](<https://github.com/Aurora2050/CoBay-CPD>)