Flexible Spatio-Temporal Hawkes Process Models for Earthquake Occurrences
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Abstract (arXiv)
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 existing methods with Hawkes process cannot fully capture. This study introduces novel nonparametric Hawkes process models that are flexible in three distinct ways. First, we incorporate the spatial inhomogeneity of the self-excitation earthquake productivity. Second, we consider the anisotropy in aftershock occurrences. Third, we reflect the space-time interactions between aftershocks with a non-separable spatio-temporal triggering structure. For model estimation, we extend the model-independent stochastic declustering (MISD) algorithm and suggest substituting its histogram-based estimators with kernel methods. We demonstrate the utility of the proposed methods by applying them to the seismicity data in regions with active seismic activities.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Oct 2022.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 1; 2026: 3.
6 papers.
- 2024Flexible Parametric Inference for Space-Time Hawkes Processescited by 3
- 2025Advances in Temporal Point Processes: Bayesian, Neural, and LLM Approachescited by 2
- 2023Hawkes-based cryptocurrency forecasting via Limit Order Book datacited by 1
- 2026Continuous-Time Reinforcement Learning for Controlled Hawkes Jump-Diffusionscited by 1
- 2026Multivariate Spatio-Temporal Neural Hawkes Processescited by 0
- 2026Modeling Patient Care Trajectories with Transformer Hawkes Processescited by 0
- 2026Continuous-Time Reinforcement Learning for Controlled Hawkes Jump-Diffusions19 Aug 2026
- 2026Modeling Patient Care Trajectories with Transformer Hawkes Processes7 Apr 2026
- 2026Multivariate Spatio-Temporal Neural Hawkes Processes27 Feb 2026
- 2025Advances in Temporal Point Processes: Bayesian, Neural, and LLM Approaches24 Jan 2025
- 2024Flexible Parametric Inference for Space-Time Hawkes Processes10 Jun 2024
- 2023Hawkes-based cryptocurrency forecasting via Limit Order Book data21 Dec 2023