Abstract by Camille Carter
Bayesian Inference of Earthquake Parameters Using Ground Motion Data
Inferring the source parameters of an earthquake in the absence of seismological data is a difficult problem in geology. We use Bayesian methods and Metropolis Hastings sampling to estimate the location, magnitude, and geometry of an 1852 Indonesian earthquake. We give an overview of the ground motion prediction models and our algorithm and demonstrate its results.