Title :
A hierarchical Bayesian nonlinear time series prediction weighted by marginal likelihoods
Author :
Saito, M. ; Asano, M. ; Matsumoto, T.
Author_Institution :
Dept. of Electr., Electron. & Comput. Eng., Waseda Univ., Tokyo, Japan
Abstract :
A nonlinear time series prediction scheme is proposed with a combination of model dynamical systems weighted by model marginal likelihoods. The scheme outperforms prediction with a single model prediction with the highest marginal likelihood
Keywords :
Bayes methods; nonlinear dynamical systems; time series; hierarchical Bayesian nonlinear time series prediction; marginal likelihoods; model dynamical systems; model marginal likelihoods; Bayesian methods; Chaos; Equations; Markov processes; Multilayer perceptrons; Neural networks; Nonlinear dynamical systems; Predictive models; Uncertainty;
Conference_Titel :
Neural Networks for Signal Processing X, 2000. Proceedings of the 2000 IEEE Signal Processing Society Workshop
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-6278-0
DOI :
10.1109/NNSP.2000.889368
