Identifying Dynamic Changes in Megathrust Segmentation via Poisson Mixture Model

Analysis of dynamic changes is one of the important information in earthquake prediction models. The earthquake frequency occurrence is often taken as data to identify the dynamic changes in large earthquake sources. The commonly used probability distribution for the counting process is the Poisson distribution. However, overdispersion relative to the Poisson distribution is often found when its average value is less than variance. The purpose of this research is to obtain an overview of the dynamic change mechanisms at large earthquake source in megathrust segment, due to possible overdispersion case. One method that can be used to solve this problem is a Poisson mixture model. This method is designed to identify unobserved heterogeneity or dynamics in the data. Here, we focus on the dynamic changes in the large earthquake sources in the Sunda megathrust segmentation on the island of Sumatra. Our results show that the Poisson mixture model is able to provide a description of the dynamic changes in that area. Especially for that area, the level of dynamic change can be classified into seven categories. For five large earthquake sources in that area, various categories of dynamic changes are found to be different from two until six categories. (paper)