A joint modeling approach for spatial earthquake risk variations

Chun Shu Chen, Hong Ding Yang

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)1733-1741
Number of pages9
JournalJournal of Applied Statistics
Volume38
Issue number8
DOIs
Publication statusPublished - 2011 Aug 1

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Joint Modeling
Earthquake
Shock
Hierarchical Bayesian Model
Conditional Model
Spatial Process
Monte Carlo Techniques
Stochastic Algorithms
Spatial Model
Spatial Pattern
Taiwan
Autoregressive Model
Markov Chain Monte Carlo
Modeling
Earthquake risk
Spatial variation

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

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A joint modeling approach for spatial earthquake risk variations. / Chen, Chun Shu; Yang, Hong Ding.

In: Journal of Applied Statistics, Vol. 38, No. 8, 01.08.2011, p. 1733-1741.

Research output: Contribution to journalArticle

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