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A hierarchical Bayesian nonlinear time series prediction weighted by marginal likelihoods

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3 Author(s)
Saito, M. ; Dept. of Electr., Electron. & Comput. Eng., Waseda Univ., Tokyo, Japan ; Asano, M. ; Matsumoto, T.

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

Published in:

Neural Networks for Signal Processing X, 2000. Proceedings of the 2000 IEEE Signal Processing Society Workshop  (Volume:1 )

Date of Conference:

2000

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