Bayesian time series models

Rubriek: Textual/Printed/Reference Materials - Boek

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'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.

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Taal: en

Bindwijze: Hardcover

Oorspronkelijke releasedatum: 11 augustus 2011

Aantal pagina's: 432

Illustraties: Nee

Hoofdauteur: David Barber

Tweede Auteur: A Taylan Cemgil

Hoofdredacteur: David Barber

Tweede Redacteur: A. Taylan Cemgil

Co Redacteur: Silvia Chiappa

Hoofduitgeverij: Cambridge University Press

Editie: New edition

Extra groot lettertype: Nee

Product breedte: 180 mm

Product hoogte: 27 mm

Product lengte: 254 mm

Studieboek: Nee

Verpakking breedte: 175 mm

Verpakking hoogte: 254 mm

Verpakking lengte: 250 mm

Verpakkingsgewicht: 912 g

EAN: 9780521196765

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