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Bernoulli race particle filters

Abstract:

When the weights in a particle filter are not available analytically, standard resampling methods cannot be employed. To circumvent this problem state-of-the-art algorithms replace the true weights with non-negative unbiased estimates. This algorithm is still valid but at the cost of higher variance of the resulting filtering estimates in comparison to a particle filter using the true weights. We propose here a novel algorithm that allows for resampling according to the true intractable weigh...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Statistics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Statistics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Statistics
Oxford college:
Hertford College
Role:
Author
ORCID:
0000-0002-7662-419X
Publisher:
MLR Press Publisher's website
Volume:
89
Pages:
2350-2358
Publication date:
2019-04-11
Acceptance date:
2018-12-22
Pubs id:
pubs:962941
URN:
uri:bf5055fa-1825-4005-a4ff-c8d1c6c3f088
UUID:
uuid:bf5055fa-1825-4005-a4ff-c8d1c6c3f088
Local pid:
pubs:962941

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