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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Liverani, Silvia Papavasiliou, Anastasia |
| Copyright Year | 2006 |
| Description | Author affiliation: University of Warwick, Department of Statistics, Coventry, CV4 7AL (Liverani, Silvia; Papavasiliou, Anastasia) |
| Abstract | We propose a particle filter for the estimation of a partially observed Markov chain that has a non dynamic component. Such systems arise when we include unknown parameters or when we decompose non ergodic systems to their ergodic classes. Our main assumption is that the value of the non dynamic component determines the limiting distribution of the observation process. In such cases, we do not want to resample the particles that correspond to the non dynamic component of the Markov chain. Instead, we take a weighted average of particle filters corresponding to different values of the non dynamic component. The computation of the weights is based on entropy and the number of particles corresponding to each particle filter is proportional to the weights. |
| Starting Page | 87 |
| Ending Page | 90 |
| File Size | 1162864 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424405794 |
| DOI | 10.1109/NSSPW.2006.4378826 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-09-13 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Parameter estimation Entropy Particle filters Adaptive estimation Nonlinear dynamical systems Random variables Distributed computing State estimation Statistics Kernel |
| Content Type | Text |
| Resource Type | Article |
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