Journal ArticleDOI
Statistical Models for Earthquake Occurrences and Residual Analysis for Point Processes
TLDR
Several classes of stochastic models for the origin times and magnitudes of earthquakes are discussed and the utility of seismic quiescence for the prediction of a major earthquake is investigated.Abstract:
This article discusses several classes of stochastic models for the origin times and magnitudes of earthquakes. The models are compared for a Japanese data set for the years 1885–1980 using likelihood methods. For the best model, a change of time scale is made to investigate the deviation of the data from the model. Conventional graphical methods associated with stationary Poisson processes can be used with the transformed time scale. For point processes, effective use of such residual analysis makes it possible to find features of the data set that are not captured in the model. Based on such analyses, the utility of seismic quiescence for the prediction of a major earthquake is investigated.read more
Citations
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The Centenary of the Omori Formula for a Decay Law of Aftershock Activity
TL;DR: In this article, the problem of fitting the modified Omori formula and related point process models to observational data is discussed mainly, and the problems of fitting these formulae to the observational data are discussed mainly.
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Space-Time Point-Process Models for Earthquake Occurrences
TL;DR: Several space-time statistical models are constructed based on both classical empirical studies of clustering and some more speculative hypotheses, and the goodness-of-fit of the models, as measured by AIC values, is discussed for two high quality data sets, in different tectonic regions as mentioned in this paper.
Journal ArticleDOI
A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects.
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The Statistical Analysis of Recurrent Events
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References
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A General Definition of Residuals
David Cox,E. J. Snell +1 more
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