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This paper extends the existing fractional Hawkes process to better model mainshock-aftershock sequences of earthquakes. The fractional Hawkes process is a self-exciting point process model with temporal decay kernel being a Mittag-Leffler…

Applications · Statistics 2026-04-13 Louis Davis , Boris Baeumer , Ting Wang

Self-exciting Hawkes processes are used to model events which cluster in time and space, and have been widely studied in seismology under the name of the Epidemic Type Aftershock Sequence (ETAS) model. In the ETAS framework, the occurrence…

Computation · Statistics 2020-02-06 Aleksandar A. Kolev , Gordon J. Ross

The Hawkes process is a versatile stochastic model for point patterns that exhibit self-excitation, that is, the property that an event occurrence increases the rate of occurrence for some period of time in the future. We present a Bayesian…

Methodology · Statistics 2025-12-01 Hyotae Kim , Athanasios Kottas

Hawkes process is one of the most commonly used models for investigating the self-exciting nature of earthquake occurrences. However, seismicity patterns have complicated characteristics due to heterogeneous geology and stresses, for which…

Applications · Statistics 2023-02-15 Junhyeon Kwon , Yingcai Zheng , Mikyoung Jun

The event sequence of many diverse systems is represented as a sequence of discrete events in a continuous space. Examples of such an event sequence are earthquake aftershock events, financial transactions, e-commerce transactions, social…

Machine Learning · Computer Science 2021-04-23 Jayesh Malaviya

Earthquakes in seismological catalogs and acoustic emission events in lab experiments can be statistically described as a linear Hawkes point process, where the spatio-temporal rate of events is a linear superposition of background…

Geophysics · Physics 2020-05-05 Jordi Baró

Several recent works point out that the crowd of small unobservable earthquakes (with magnitudes below the detection threshold $m_d$) may play a significant and perhaps dominant role in triggering future seismicity. Using the ETAS branching…

Geophysics · Physics 2007-12-04 A. Saichev , D. Sornette

Predicting discrete events in time and space has many scientific applications, such as predicting hazardous earthquakes and outbreaks of infectious diseases. History-dependent spatio-temporal Hawkes processes are often used to…

Machine Learning · Computer Science 2023-01-31 Negar Erfanian , Santiago Segarra , Maarten de Hoop

The Hawkes process is a class of point processes whose future depends on their own history. Previous theoretical work on the Hawkes process is limited to a special case in which a past event can only increase the occurrence of future…

Methodology · Statistics 2019-06-21 Shizhe Chen , Ali Shojaie , Eric Shea-Brown , Daniela Witten

In statistical seismology, the Epidemic Type Aftershocks Sequence (ETAS) model is a branching process used world-wide to forecast earthquake intensity rates and reproduce many statistical features observed in seismicity catalogs. In this…

Geophysics · Physics 2023-01-09 Lorenzo Cristofaro , Roberto Garra , Enrico Scalas , Ilaria Spassiani

We characterize a Hawkes point process with kernel proportional to the probability density function of Mittag-Leffler random variables. This kernel decays as a power law with exponent $\beta +1 \in (1,2]$. Several analytical results can be…

Hawkes processes are a self-exciting stochastic process used to describe phenomena whereby past events increase the probability of the occurrence of future events. This work presents a flexible approach for modelling a variant of these,…

Methodology · Statistics 2022-08-08 Raiha Browning , Judith Rousseau , Kerrie Mengersen

Univariate marked Hawkes processes are used to model a range of real-world phenomena including earthquake aftershock sequences, contagious disease spread, content diffusion on social media platforms, and order book dynamics. This paper…

Methodology · Statistics 2026-04-13 Louis Davis , Conor Kresin , Boris Baeumer , Ting Wang

Epidemic-Type Aftershock Sequence (ETAS) models are point processes that have found prominence in seismological modeling. Its success has led to the development of a number of different versions of the ETAS model. Among these extensions is…

Applications · Statistics 2022-07-06 Tom Stindl , Feng Chen

We propose a new physically-based ``multifractal stress activation'' model of earthquake interaction and triggering based on two simple ingredients: (i) a seismic rupture results from activated processes giving an exponential dependence on…

Statistical Mechanics · Physics 2007-05-23 G. Ouillon , D. Sornette

Point processes have been dominant in modeling the evolution of seismicity for decades, with the Epidemic Type Aftershock Sequence (ETAS) model being most popular. Recent advances in machine learning have constructed highly flexible point…

Geophysics · Physics 2023-10-04 Samuel Stockman , Daniel J. Lawson , Maximilian J. Werner

Multivariate Hawkes Processes (MHPs) are an important class of temporal point processes that have enabled key advances in understanding and predicting social information systems. However, due to their complex modeling of temporal…

Machine Learning · Computer Science 2020-03-02 Maximilian Nickel , Matthew Le

As a tool for capturing irregular temporal dependencies (rather than resorting to binning temporal observations to construct time series), Hawkes processes with exponential decay have seen widespread adoption across many application…

Machine Learning · Computer Science 2021-04-05 Tiago Santos , Florian Lemmerich , Denis Helic

Aftershocks of aftershocks - and their aftershock cascades - substantially contribute to the increased seismicity rate and the associated elevated seismic hazard after the occurrence of a large earthquake. Current state-of-the-art…

Geophysics · Physics 2024-11-07 Leila Mizrahi , Dario Jozinović

We propose a new version of the ETAS model, which we also analyze theoretically. As for the standard ETAS model, we assume the Gutenberg-Richter law as a probability density function for background events' magnitude. Instead, the magnitude…

Probability · Mathematics 2015-04-23 Ilaria Spassiani , Giovanni Sebastiani
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