- Abstract:
-
In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed. We sh...
Expand abstract - Publication status:
- Published
- Journal:
- STATISTICS AND COMPUTING
- Volume:
- 10
- Issue:
- 3
- Pages:
- 197-208
- Publication date:
- 2000-07-05
- DOI:
- ISSN:
-
0960-3174
- URN:
-
uuid:2f2825fc-9e6f-4888-a7ab-4e65a4be97a2
- Source identifiers:
-
190630
- Local pid:
- pubs:190630
- Copyright date:
- 2000
Journal article
On sequential Monte Carlo sampling methods for Bayesian filtering
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