Abstract
Most seismic risk studies assume the occurrences of large earthquakes follow a memoryless Poisson Process. Yet, current scientific knowledge describes earthquake occurrences as a memory process of gradual accumulation and sudden release of energy. After reviewing some suggested models for earthquake occurrence, two stochastic models with memory, the Linearly Increasing Hazard Rate (LIHR) model and a continuous time Markov chain model, are offered as simpler alternatives. Using earthquake occurrence data from Lima, Peru, the LIHR model is tested against the Poisson and found to provide a significantly better fit. Some implications of the use of memory processes for insurance and reinsurance problems are explored.
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