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Multivariate Hawkes process provides a powerful framework for modeling temporal dependencies and event-driven interactions in complex systems. While existing methods primarily focus on uncovering causal structures among observed…

Machine Learning · Computer Science 2026-03-03 Songyao Jin , Biwei Huang

In this paper we study the frequentist properties of Bayesian approaches in linear high dimensional Hawkes processes in a sparse regime where the number of interaction functions acting on each component of the Hawkes process is much smaller…

Statistics Theory · Mathematics 2025-10-29 Judith Rousseau , Vincent Rivoirard , Déborah Sulem

We propose a fast and efficient estimation method that is able to accurately recover the parameters of a d-dimensional Hawkes point-process from a set of observations. We exploit a mean-field approximation that is valid when the…

Machine Learning · Computer Science 2016-04-20 Emmanuel Bacry , Stéphane Gaïffas , Iacopo Mastromatteo , Jean-François Muzy

We introduce a multivariate Hawkes process with constraints on its conditional density. It is a multivariate point process with conditional intensity similar to that of a multivariate Hawkes process but certain events are forbidden with…

Applications · Statistics 2014-02-14 Ban Zheng , François Roueff , Frédéric Abergel

Many events occur in the world. Some event types are stochastically excited or inhibited---in the sense of having their probabilities elevated or decreased---by patterns in the sequence of previous events. Discovering such patterns can help…

Machine Learning · Computer Science 2017-11-22 Hongyuan Mei , Jason Eisner

In this work, several convergence results are established for nearly critical self-excited systems in which event arrivals are described by multivariate marked Hawkes point processes. Under some mild high-frequency assumptions, the rescaled…

Probability · Mathematics 2024-01-31 Wei Xu

We study statistical aspects of state-dependent Hawkes processes, which are an extension of Hawkes processes where a self- and cross-exciting counting process and a state process are fully coupled, interacting with each other. The…

Statistical Finance · Quantitative Finance 2021-09-17 Maxime Morariu-Patrichi , Mikko S. Pakkanen

Asynchronous events sequences are widely distributed in the natural world and human activities, such as earthquakes records, users activities in social media and so on. How to distill the information from these seemingly disorganized data…

Machine Learning · Computer Science 2021-12-30 Lu-ning Zhang , Jian-wei Liu , Zhi-yan Song , Xin Zuo

We consider a sequence of Hawkes processes whose excitation measures may depend on the generation, and study its scaling limits in the near-unstable limiting regime. The limiting random measures, characterized via a nonlinear convolutional…

Probability · Mathematics 2026-04-08 Tristan Pace , Gordan Zitkovic

Both Hawkes processes and autoregressive processes rely on linear functionals of their past, while modeling different types of data. Since datasets arising from observations of the same phenomenon may be heterogeneous and sampled at…

Probability · Mathematics 2026-05-28 Théo Leblanc

The Hawkes process is a self-exciting sample point process. It has wide applications in finance, social networks, criminology, seismology, and many other fields. With the development of storage technology, data-driven models are attracting…

Probability · Mathematics 2021-06-23 Haixu Wang

This paper introduces the Hawkes skeleton and the Hawkes graph. These objects summarize the branching structure of a multivariate Hawkes point process in a compact, yet meaningful way. We demonstrate how graph-theoretic vocabulary…

Methodology · Statistics 2017-06-14 Paul Embrechts , Matthias Kirchner

This paper proposes a new approach for change point detection in multivariate Hawkes processes using Fr\'echet statistic of a network. The method splits the point process into overlapping windows, estimates kernel matrices in each window,…

Machine Learning · Statistics 2025-01-23 Rui Luo , Vikram Krishnamurthy

We study the continuous time limit of a self-exciting negative binomial process and discuss the critical properties of its intensity distribution. In this limit, the process transforms into a marked Hawkes process. The probability mass…

Probability · Mathematics 2023-05-24 Kotaro Sakuraba , Wataru Kurebayashi , Masato Hisakado , Shintaro Mori

We propose a novel approach to marked Hawkes kernel inference which we name the moment-based neural Hawkes estimation method. Hawkes processes are fully characterized by their first and second order statistics through a Fredholm integral…

Trading and Market Microstructure · Quantitative Finance 2026-02-02 Timothée Fabre , Ioane Muni Toke

We consider the problem of estimating the parameters of a non-stationary Hawkes process with time-dependent reproduction rate and baseline intensity. Our approach relies on the standard maximum likelihood estimator (MLE), coinciding with…

Statistics Theory · Mathematics 2025-06-04 Thomas Deschatre , Pierre Gruet , Antoine Lotz

This paper presents a parametric estimation method for ill-observed linear stationary Hawkes processes. When the exact locations of points are not observed, but only counts over time intervals of fixed size, methods based on the likelihood…

Statistics Theory · Mathematics 2022-01-11 Felix Cheysson , Gabriel Lang

Aggressive behavior in autistic inpatient youth often arises in temporally clustered bursts complicating efforts to distinguish external triggers from internal escalation. The sample population branching factor-the expected number of new…

In this paper, we build a model for biological neural nets where the activity of the network is described by Hawkes processes having a variable length memory. The particularity of this paper is to deal with an infinite number of components.…

Probability · Mathematics 2015-09-18 Pierre Hodara , Eva Löcherbach

We prove a central limit type theorem for critical marked Hawkes processes. We study the case where the marks are i.i.d. with nonnegative values and their common distribution is either heavy tailed or has finite variance. The kernel…

Probability · Mathematics 2026-05-05 Anna Talarczyk