Bayesian Time Series Models (Hardcover)
Language: English
Published by Cambridge University Press, Cambridge, 2011
- Hardcover
- New

Seller: CitiRetail, Stevenage, United KingdomCitiRetail
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Condition: New
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Hardcover. 'What's going to happen next?' Time series data hold the answers, and Bayesian methods represent the cutting edge in learning what they have to say. This ambitious book is the first unified treatment of the emerging knowledge-base in Bayesian time series techniques. Exploiting the unifying framework of probabilistic graphical models, the book covers approximation schemes, both Monte Carlo and deterministic, and introduces switching, multi-object, non-parametric and agent-based models in a variety of application environments. It demonstrates that the basic framework supports the rapid creation of models tailored to specific applications and gives insight into the computational complexity of their implementation. The authors span traditional disciplines such as statistics and engineering and the more recently established areas of machine learning and pattern recognition. Readers with a basic understanding of applied probability, but no experience with time series analysis, are guided from fundamental concepts to the state-of-the-art in research and practice. 'What's going to happen next?' Time series data hold the answers. This ambitious book is the first unified treatment of the emerging knowledge-base in Bayesian time series techniques. Readers with only a basic understanding of applied probability are guided from fundamental concepts to the state-of-the-art in research and practice. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
Seller Inventory # 9780521196765
- Title
- Bayesian Time Series Models (Hardcover)
- Author
- David Barber
- Publisher
- Cambridge University Press, Cambridge
- Publication year
- 2011
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0521196760
- ISBN 13
- 9780521196765
"Synopsis" may belong to another edition of this title.
About the Author
A. Taylan Cemgil is an Assistant Professor in the Department of Computer Engineering at Boğaziçi University, Istanbul.
Silvia Chiappa is a Marie Curie Fellow at the Statistical Laboratory, Cambridge.
"About the title" may belong to another edition of this title.
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