A Bayesian-Decision Theoretic Approach to Model Error Modeling.

McVinish, Ross S., Braslavsky, .Julio H. and Mengersen, Kerrie L. (2006). A Bayesian-Decision Theoretic Approach to Model Error Modeling.. In: Proceedings of the 14th IFAC Symposium on System Identification - SYSID-2006. Symposium on System Identification, Newscastle, Australia, (1015-1020). 29 - 31 March, 2006.


Author McVinish, Ross S.
Braslavsky, .Julio H.
Mengersen, Kerrie L.
Title of paper A Bayesian-Decision Theoretic Approach to Model Error Modeling.
Conference name Symposium on System Identification
Conference location Newscastle, Australia
Conference dates 29 - 31 March, 2006
Proceedings title Proceedings of the 14th IFAC Symposium on System Identification - SYSID-2006
Publication Year 2006
Sub-type Fully published paper
Start page 1015
End page 1020
Total pages 6
Language eng
Abstract/Summary Abstract: This paper takes a Bayesian-decision theoretic approach to transfer function estimation, nominal model estimation, and quantification of the resulting model error. Consistency of the nonparametric estimate of the transfer function is proved together with a rate of convergence. The required quantities can be computed routinely using reversible jump Markov chain Monte Carlo methods. The proposed methodology has connections with set membership identification which has been extensively studied for this problem.
Subjects 010405 Statistical Theory
Keyword Transfer functions
Decision theory
Non-parametric identification
Monte Carlo calculation
loss minimization
Q-Index Code EX

 
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Created: Wed, 04 Feb 2009, 11:23:34 EST by Judy Dingwall on behalf of Mathematics