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Springer Series in Statistics

Bayesian Forecasting and Dynamic Models

Authors: West, Mike, Harrison, Jeff

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About this book

In this book we are concerned with Bayesian learning and forecast­ ing in dynamic environments. We describe the structure and theory of classes of dynamic models, and their uses in Bayesian forecasting. The principles, models and methods of Bayesian forecasting have been developed extensively during the last twenty years. This devel­ opment has involved thorough investigation of mathematical and sta­ tistical aspects of forecasting models and related techniques. With this has come experience with application in a variety of areas in commercial and industrial, scientific and socio-economic fields. In­ deed much of the technical development has been driven by the needs of forecasting practitioners. As a result, there now exists a relatively complete statistical and mathematical framework, although much of this is either not properly documented or not easily accessible. Our primary goals in writing this book have been to present our view of this approach to modelling and forecasting, and to provide a rea­ sonably complete text for advanced university students and research workers. The text is primarily intended for advanced undergraduate and postgraduate students in statistics and mathematics. In line with this objective we present thorough discussion of mathematical and statistical features of Bayesian analyses of dynamic models, with illustrations, examples and exercises in each Chapter.

Reviews

"The authors are well known to anyone with an interest in forecasting and time series modelling.... Anyone familiar with the authors' work will wish to read this book."
(Mathematical Reviews)

Table of contents (16 chapters)

Table of contents (16 chapters)

Buy this book

eBook $74.99
price for USA in USD (gross)
  • ISBN 978-1-4757-9365-9
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
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Bibliographic Information

Bibliographic Information
Book Title
Bayesian Forecasting and Dynamic Models
Authors
Series Title
Springer Series in Statistics
Copyright
1989
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-1-4757-9365-9
DOI
10.1007/978-1-4757-9365-9
Series ISSN
0172-7397
Edition Number
1
Number of Pages
XXI, 704
Topics

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