The quest to find successful methods to forecast earthquakes has proven to be very challenging. Useful earthquake forecasts require detailed specification of a number of variables, namely the epicenter, depth, time, and magnitude of the coming earthquake. While forecasting the times of strong aftershocks within the rupture zone of a strong earthquake has been developed with some success (e.g., Reasenberg and Jones 1989, 1994), forecasting the times of future strong earthquakes, even when their locations are known to occur within broad geographic areas, has not been very successful. The apparent success of the M8 algorithm in...
Non-Poissonian Earthquake Clustering and the Hidden Markov Model as Bases for Earthquake Forecasting in California
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John E. Ebel, Daniel W. Chambers, Alan L. Kafka, Jenny A. Baglivo; Non-Poissonian Earthquake Clustering and the Hidden Markov Model as Bases for Earthquake Forecasting in California. Seismological Research Letters ; 78 (1): 57–65. doi: https://doi.org/10.1785/gssrl.78.1.57
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