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January 1, 1970Journal of the Royal Statistical Society Series B (Statistical Methodology)394 citations

Stochastic Models for Earthquake Occurrence

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DVD. Vere‐Jones

Key Points

  • The paper aims to survey stochastic models for predicting earthquake energies and times in specific regions.
  • Describes stochastic point processes and their suitability for earthquake modeling.
  • Focuses on clustering models such as Neymann–Scott and Bartlett–Lewis for earthquake data analysis.
  • Illustrates applications using earthquake data from New Zealand.
  • Highlights the effectiveness of stochastic models in approximating point events for earthquakes.
  • Covers models for aftershock sequences that follow large earthquakes.

Abstract

Summary This paper attempts to survey some of the stochastic models which have been proposed for the sequence of energies and origin times of earthquakes from a given region, and to describe some examples of their application. to a good approximation in a regional study, each earthquake may be regarded as a point event, and consequently the main emphasis is on stochastic point processes. The theory of such processes is developed in a form suitable for this context, with particular emphasis being given to the clustering models of Neymann–Scott and Bartlett–Lewis. The use of these models is illustrated with reference to earthquake data from New Zealand. A final Section is concerned with stochastic models for aftershock sequences—the trains of smaller shocks which frequently follow the occurrence of large shallow earthquakes.

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Cite This Study

D. Vere‐Jones (1970) studied this question.

synapsesocial.com/papers/6a1bc8e1b33628da419cdb12https://doi.org/10.1111/j.2517-6161.1970.tb00814.x
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