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Item Details
Title: BAYESIAN FORECASTING AND DYNAMIC MODELS
By: Mike West, Jeff Harrison
Format: Hardback

List price: £109.99


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ISBN 10: 0387947256
ISBN 13: 9780387947259
Publisher: SPRINGER-VERLAG NEW YORK INC.
Pub. date: 26 March, 1999
Edition: 2nd ed. 1997. Corr. 2nd printing 1999
Series: Springer Series in Statistics
Pages: 696
Description: This edition features revised, updated and additional material on the structure, theory and application of classes of dynamic models in Bayesian time series analysis and forecasting. This edition also contains more exercises and covers new topics at the research and application frontiers.
Synopsis: This text is concerned with Bayesian learning, inference and forecasting in dynamic environments. We describe the structure and theory of classes of dynamic models and their uses in forecasting and time series analysis. The principles, models and methods of Bayesian forecasting and time - ries analysis have been developed extensively during the last thirty years. Thisdevelopmenthasinvolvedthoroughinvestigationofmathematicaland statistical aspects of forecasting models and related techniques. With this has come experience with applications in a variety of areas in commercial, industrial, scienti?c, and socio-economic ?elds. Much of the technical - velopment has been driven by the needs of forecasting practitioners and applied researchers. As a result, there now exists a relatively complete statistical and mathematical framework, presented and illustrated here. In writing and revising this book, our primary goals have been to present a reasonably comprehensive view of Bayesian ideas and methods in m- elling and forecasting, particularly to provide a solid reference source for advanced university students and research workers.
Illustrations: biography
Publication: US
Imprint: Springer-Verlag New York Inc.
Returns: Returnable
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