Wang, B. and Titterington, D.M. (2004) Lack of consistency of mean field and variational Bayes approximations for state space models. Neural Processing Letters, 20 (3). pp. 151-170. ISSN 1573-773X
Abstract
The consistency problem of both mean field and variational Bayes estimators in the context of linear state space models is investigated. We prove that the mean field approximation is asymptotically consistent when the variances of the noise variables in the system are sufficiently small, but neither the mean field estimator nor the variational Bayes estimator is always asymptotically consistent as the lsquosample sizersquo becomes large. The lsquogaprsquo between the estimators and the true values is roughly estimated.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Mathematics (York) |
Depositing User: | York RAE Import |
Date Deposited: | 09 Mar 2009 19:51 |
Last Modified: | 09 Mar 2009 19:51 |
Published Version: | http://dx.doi.org/10.1007/s11063-004-2024-6 |
Status: | Published |
Publisher: | Springer US |
Identification Number: | 10.1007/s11063-004-2024-6 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:7108 |