An edition of Bayesian time series models (2011)

Bayesian Time Series Models

Bayesian Time Series Models
David Barber, Ali Taylan Cemgi ...
Not in Library

My Reading Lists:

Create a new list

Check-In

×Close
Add an optional check-in date. Check-in dates are used to track yearly reading goals.
Today


Buy this book

Last edited by MARC Bot
September 25, 2020 | History
An edition of Bayesian time series models (2011)

Bayesian Time Series Models

"'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"--

"Time series appear in a variety of disciplines, from finance to physics, computer science to biology. The origins of the subject and diverse applications in the engineering and physics literature at times obscure the commonalities in the underlying models and techniques. A central aim of this book is an attempt to make modern time series techniques accessible to a broad range of researchers, based on the unifying concept of probabilistic models. These techniques facilitate access to the modern time series literature, including financial time series prediction, video-tracking, music analysis, control and genetic sequence analysis. A particular feature of the book is that it brings together leading researchers that span the more traditional disciplines of statistics, control theory, engineering and signal processing,to the more recent area machine learning and pattern recognition"--

Publish Date
Language
English
Pages
434

Buy this book

Edition Availability
Cover of: Bayesian Time Series Models
Bayesian Time Series Models
2012, Cambridge University Press
in English
Cover of: Bayesian Time Series Models
Bayesian Time Series Models
2012, Cambridge University Press
in English
Cover of: Bayesian Time Series Models
Bayesian Time Series Models
2011, Cambridge University Press
in English
Cover of: Bayesian Time Series Models
Bayesian Time Series Models
2011, Cambridge University Press
in English
Cover of: Bayesian time series models
Bayesian time series models
2011, Cambridge University Press
in English

Add another edition?

Book Details


Classifications

Dewey Decimal Class
519.5/5

ID Numbers

Open Library
OL53953811M
ISBN 13
9781280775932

Source records

Better World Books record

Community Reviews (0)

Feedback?
No community reviews have been submitted for this work.

Lists

This work does not appear on any lists.

History

Download catalog record: RDF / JSON
September 25, 2020 Edited by MARC Bot import existing book
October 27, 2011 Edited by LC Bot import new book
October 21, 2011 Created by LC Bot import new book