Towards smooth particle filters for likelihood estimation with multivariate latent variables
In parametrized continuous state-space models, one can obtain estimates of the likelihood of the data for fixed parameters via the Sequential Monte Carlo methodology. Unfortunately, even if the likelihood is continuous in the parameters, the estimates produced by practical particle filters are not,...
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| Format: | Others |
| Language: | English |
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University of British Columbia
2008
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| Online Access: | http://hdl.handle.net/2429/1547 |