Correla\c{c}\~ao de longa-dura\c{c}\~ao e anal\'ise bayesiana da evolu\c{c}\~ao temporal dos terremotos ao longo da falha de samambaia, nordeste do brasil

TL;DR

This paper employs a Bayesian approach with MCMC methods to analyze the long-term seismic activity along the Samambaia fault in Brazil, providing insights into earthquake occurrence patterns over 15 years.

Contribution

It introduces a Bayesian model for seismic event occurrence times conditioned on magnitudes, integrating physical and historical data, and applies MCMC for posterior inference.

Findings

Posterior confidence bands for seismic intensity over time.

Estimated mean occurrence rate of earthquakes.

Bayesian model effectively captures seismic activity patterns.

Abstract

A Bayesian approach is adopted to analyze the sequence of seismic events and their magnitudes near Jo\~ao C\^amara which occurred mainly from 1983 to 1998 along the Samambaia fault. In this work, we choose a Bayesian model for the process of occurrence times conditional on the observed magnitude values following the same procedure suggested by Stavrakakis and Tselentis (1987). The model parameters are determined on the basis of historical and physical information. We generate posterior samples from the joint posterior distribution of the model parameters by using a variant of the Metropolis-Hastings algorithm. We use the results in a variety of ways, including the construction of pointwise posterior confidence bands for the conditional intensity of the point process as a function of time, as well as, a posterior distribuition as a function of the mean of occurrence per unit time.