Optimal filtering and the dual process
Duration: 34 mins 40 secs
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| Description: |
Papaspiliopoulos, O (Institució Catalana de Recerca i Estudis Avançats (ICREA))
Thursday 24 April 2014, 16:25-17:00 |
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| Created: | 2014-04-28 17:21 |
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| Collection: | Advanced Monte Carlo Methods for Complex Inference Problems |
| Publisher: | Isaac Newton Institute |
| Copyright: | Papaspiliopoulos, O |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
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| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | Co-author: Matteo Ruggiero (Turin)
We link optimal filtering for hiddenMarkov models to the notion of duality forMarkov processes.We show that when the signal is dual to a process that has two components, one deterministic and one a pure death process, and with respect to functions that define changes of measure conjugate to the emission density, the filtering distributions evolve in the family of finite mixtures of such measures and the filter can be computed at a cost that is polynomial in the number of observations. Special cases of our framework include the Kalman filter, and computable filters for the Cox–Ingersoll–Ross process and the one-dimensional Wright– Fisher process, which have been investigated before in the literature. The dual we obtain for the Cox– Ingersoll–Ross process appears to be new in the literature. Related Links: http://www.isi-web.org/images/bernoulli/BEJ1305-022.pdf - article |
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