[STT52-04] Prediction of Aftershocks With Gaussian Process Regression: Application to the 2004 Chuetsu Earthquake
Keywords:Bayesian method, detection-rate function, gaussian process regression
To overcome the difficulty, we incorporate a detection function into the likelihood, and apply the gaussian process regression, which is a Bayesian and nonparametric method, to the detection function. The gaussian process regression has been drawing an attention due to the largeness of the functional class that can represent, in fact, it has recently been known that it has some relations with deep learning. With the use of gaussian process regression, not only the parameter of the distribution of the aftershocks and the detection function, but the credible interval of the parameters and the detection function can be also obtained. We have also proposed a Bayesian computational algorithm to compute the hyperparameters. Our proposed method is applied to the 2004 Chuetsu earthquake.