Bayesian Time Series Models - Barber, David (Editor), and Cemgil, A. Taylan (Editor), and Chiappa, Silvia (Editor)
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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 ...

Bayesian Time Series Models 2011, Cambridge University Press, Cambridge

ISBN-13: 9780521196765