Bayesian Estimation of the ETAS Model for Earthquake Occurrences
Bayesian estimation of the ETAS model for earthquake occurrences
Estimate the parameters of the ETAS model using maximum likelihood.
Draws samples from the posterior distribution of the ETAS model
Simulates synthetic data from the ETAS model
Simulates event times from an inhomogenous Poisson process on [0,T]
The Epidemic Type Aftershock Sequence (ETAS) model is one of the best-performing methods for modeling and forecasting earthquake occurrences. This package implements Bayesian estimation routines to draw samples from the full posterior distribution of the model parameters, given an earthquake catalog. The paper on which this package is based is Gordon J. Ross - Bayesian Estimation of the ETAS Model for Earthquake Occurrences (2016), available from the below URL.