Estimation, Decoding and Forecasting in HMM and Hybrid HMM/ANN Models: a Case of Seismic Events in Poland

Abstract

This paper compares performance of a hidden Markov model (HMM) and a hybrid HMM/ANN model in seismic events modeling. Observation variables are assumed to follow a Poisson distribution. Parameters of the discrete-time two-state models are estimated on the basis of data on seismic events that were recorded in Poland from 1991 to 1995. Then, on the basis of the estimation results, the most likely sequences of states of the hidden Markov chains are found and forecasts for January 1996 are made. It is shown that the hybrid model fits better to the data.