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A joint modeling approach for spatial earthquake risk variations

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  • Chun-Shu Chen
  • Hong-Ding Yang

Abstract

Modeling spatial patterns and processes to assess the spatial variations of data over a study region is an important issue in many fields. In this paper, we focus on investigating the spatial variations of earthquake risks after a main shock. Although earthquake risks have been extensively studied in the literatures, to our knowledge, there does not exist a suitable spatial model for assessing the problem. Therefore, we propose a joint modeling approach based on spatial hierarchical Bayesian models and spatial conditional autoregressive models to describe the spatial variations in earthquake risks over the study region during two periods. A family of stochastic algorithms based on a Markov chain Monte Carlo technique is then performed for posterior computations. The probabilistic issue for the changes of earthquake risks after a main shock is also discussed. Finally, the proposed method is applied to the earthquake records for Taiwan before and after the Chi-Chi earthquake.

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  • Chun-Shu Chen & Hong-Ding Yang, 2011. "A joint modeling approach for spatial earthquake risk variations," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(8), pages 1733-1741, September.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:8:p:1733-1741
    DOI: 10.1080/02664763.2010.529883
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    Cited by:

    1. Hong-Ding Yang & Yun-Huan Lee & Che-Yang Lin, 2023. "On Study of the Occurrence of Earth-Size Planets in Kepler Mission Using Spatial Poisson Model," Mathematics, MDPI, vol. 11(11), pages 1-14, May.

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