Flexible spatio-temporal Hawkes process models for earthquake occurrences

被引:6
作者
Kwon, Junhyeon [1 ]
Zheng, Yingcai [2 ]
Jun, Mikyoung [1 ]
机构
[1] Univ Houston, Dept Math, Houston, TX 77004 USA
[2] Univ Houston, Dept Earth & Atmospher Sci, Houston, TX USA
基金
美国国家科学基金会;
关键词
Anisotropy; Earthquake; Hawkes process; Inhomogeneous model; Spatio-temporal nonseparability; Spatio-temporal point process; POINT-PROCESS MODELS; TIME ETAS MODEL; ESTIMATORS;
D O I
10.1016/j.spasta.2023.100728
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
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 after-shocks with a non-separable spatio-temporal triggering struc-ture. For model estimation, we extend the model-independent stochastic declustering (MISD) algorithm and suggest substitut-ing its histogram-based estimators with kernel methods. We demonstrate the utility of the proposed methods by apply-ing them to the seismicity data in regions with active seismic activities.(c) 2023 Elsevier B.V. All rights reserved.
引用
收藏
页数:23
相关论文
共 50 条
  • [1] ON BANDWIDTH VARIATION IN KERNEL ESTIMATES - A SQUARE ROOT LAW
    ABRAMSON, IS
    [J]. ANNALS OF STATISTICS, 1982, 10 (04) : 1217 - 1223
  • [2] Ahlenius H., 2022, WORLD TECTONIC PLATE
  • [3] [Anonymous], 1994, Journal of Computational and Graphical Statistics, DOI DOI 10.1080/10618600.1994.10474656
  • [4] An updated digital model of plate boundaries
    Bird, P
    [J]. GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS, 2003, 4
  • [5] Simple discrete-time self-exciting models can describe complex dynamic processes: A case study of COVID-19
    Browning, Raiha
    Sulem, Deborah
    Mengersen, Kerrie
    Rivoirard, Vincent
    Rousseau, Judith
    [J]. PLOS ONE, 2021, 16 (04):
  • [6] Daley D. J., 2003, Elementary Theory and Methods. Probability and Its Applications, V1, DOI [DOI 10.1007/B97277, 10.1007/b97277]
  • [7] Fast computation of spatially adaptive kernel estimates
    Davies, Tilman M.
    Baddeley, Adrian
    [J]. STATISTICS AND COMPUTING, 2018, 28 (04) : 937 - 956
  • [8] Tutorial on kernel estimation of continuous spatial and spatiotemporal relative risk
    Davies, Tilman M.
    Marshall, Jonathan C.
    Hazelton, Martin L.
    [J]. STATISTICS IN MEDICINE, 2018, 37 (07) : 1191 - 1221
  • [9] Diggle P. J., 2013, Chapman Hall Monographs on Statistics Applied, V3rd ed., DOI DOI 10.1201/B15326
  • [10] DETERMINATION OF EARTHQUAKE SOURCE PARAMETERS FROM WAVEFORM DATA FOR STUDIES OF GLOBAL AND REGIONAL SEISMICITY
    DZIEWONSKI, AM
    CHOU, TA
    WOODHOUSE, JH
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH, 1981, 86 (NB4): : 2825 - 2852