Path storage in the particle filter

This article considers the problem of storing the paths generated by a particle filter and more generally by a sequential Monte Carlo algorithm. It provides a theoretical result bounding the expected memory cost by T + CN log N where T is the time horizon, N is the number of particles and C is a con...

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Veröffentlicht in:Statistics and computing Jg. 25; H. 2; S. 487 - 496
Hauptverfasser: Jacob, Pierre E., Murray, Lawrence M., Rubenthaler, Sylvain
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Boston Springer US 01.03.2015
Springer Verlag (Germany)
Schlagworte:
Algorithms
Artificial Intelligence
Computation
Computational Complexity
Computer Science
Constants
Distributed, Parallel, and Cluster Computing
Mathematical models
Mathematics
Mathematics and Statistics
Monte Carlo methods
Probability
Probability and Statistics in Computer Science
Statistical Theory and Methods
Statistics
Statistics and Computing/Statistics Programs
Storage
Sequential Monte Carlo
Parallel computation
Particle filter
Memory cost
parallel computation
particle filter
memory cost
ISSN:0960-3174, 1573-1375
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:This article considers the problem of storing the paths generated by a particle filter and more generally by a sequential Monte Carlo algorithm. It provides a theoretical result bounding the expected memory cost by T + CN log N where T is the time horizon, N is the number of particles and C is a constant, as well as an efficient algorithm to realise this. The theoretical result and the algorithm are illustrated with numerical experiments.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0960-3174
1573-1375
DOI:10.1007/s11222-013-9445-x