EM-algorithm for training of state-space models with application to time series prediction
Elia Liitiäinen, Nima Reyhani and Amaury Lendasse
In: ESANN 2006, European Symposium on Artificial Neural Networks, 26-28 April 2006, Bruges (Belgium).
In this paper, an improvement to the E step of the EM algorithm for nonlinear state-space models is presented. We also propose strategies for model structure selection when the EM-algorithm and statespace models are used for time series prediction. Experiments on the Poland electricity load time series show that the method gives good shortterm
predictions and can also be used for long-term prediction.