Efficient particle filtering for jump Markov systems. Application to time-varying autoregressions
In this paper, we present an efficient particle filtering method to perform optimal estimation in jump Markov (nonlinear) systems (JMSs). Such processes consist of a mixture of heterogeneous models and possess a natural hierarchical structure. We take advantage of these specificities in order to dev...
| Main Authors: | , , |
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| Format: | Journal article |
| Published: |
2003
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