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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.
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From the Back Cover
The second edition of this book includes revised, updated, and additional material on the structure, theory, and application of classes of dynamic models in Bayesian time series analysis and forecasting.
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date1997
- ISBN 10 0387947256
- ISBN 13 9780387947259
- BindingHardcover
- LanguageEnglish
- Edition number2
- Number of pages696
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Bayesian Forecasting and Dynamic Models Springer Series in Statistics
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gebundene Ausgabe. Condition: Gut. 2. Auflage;. 680 Seiten Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber und kann entsprechende Merkmale aufweisen (Rückenschild, Instituts-Stempel.). In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 1120. Seller Inventory # 2157588
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Bayesian Forecasting and Dynamic Models
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Hardcover. Condition: As new. Second Edition. Springer Series in Statistics. xiv, 680, [1] p. 24 cm. 115 figures. Yellow hardcover. Topics: the dynamic linear model; DLM theory; polynomial trend, seasonal, regression, autoregression, and related models; multi-process models; non-linear dynamic models; exponential family dynamic models; multivariate modelling and forecasting; distribution theory and linear algebra; etc. Bibliography and index. Seller Inventory # 116416
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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. Seller Inventory # 5912159
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Bayesian Forecasting and Dynamic Models
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Springer New York Jan 1997, 1997
ISBN 10: 0387947256
ISBN 13: 9780387947259
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 700 pp. Englisch. Seller Inventory # 9780387947259
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