Bayesian Forecasting and Dynamic Models

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9780387947259: Bayesian Forecasting and Dynamic Models

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Contenuti:

to the DLM: The First-Order Polynomial Model.- to the DLM: The Dynamic Regression Model.- The Dynamic Linear Model.- Univariate Time Series DLM Theory.- Model Specification and Design.- Polynomial Trend Models.- Seasonal Models.- Regression, Autoregression, and Related Models.- Illustrations and Extensions of Standard DLMs.- Intervention and Monitoring.- Multi-Process Models.- Non-Linear Dynamic Models: Analytic and Numerical Approximations.- Exponential Family Dynamic Models.- Simulation-Based Methods in Dynamic Models.- Multivariate Modelling and Forecasting.- Distribution Theory and Linear Algebra.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

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1.

West, Mike; Harrison, Jeff
Editore: Springer (1999)
ISBN 10: 0387947256 ISBN 13: 9780387947259
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English-Book-Service Mannheim
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Descrizione libro Springer, 1999. Condizione libro: New. Codice libro della libreria UA9780387947259

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2.

MIKE WEST
Editore: Springer (1997)
ISBN 10: 0387947256 ISBN 13: 9780387947259
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Herb Tandree Philosophy Books
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Descrizione libro Springer, 1997. Hardback. Condizione libro: NEW. 9780387947259 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Codice libro della libreria HTANDREE0275548

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3.

Jeff Harrison
Editore: Springer Mrz 1999 (1999)
ISBN 10: 0387947256 ISBN 13: 9780387947259
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Descrizione libro Springer Mrz 1999, 1999. Buch. Condizione libro: Neu. 23.4x15.6x cm. 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. 682 pp. Englisch. Codice libro della libreria 9780387947259

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Mike West
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Descrizione libro Springer-Verlag New York Inc., 1999. HRD. Condizione libro: New. New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice libro della libreria I1-9780387947259

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5.

Jeff Harrison
Editore: Springer Mrz 1999 (1999)
ISBN 10: 0387947256 ISBN 13: 9780387947259
Nuovi Quantità: 1
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Rheinberg-Buch
(Bergisch Gladbach, Germania)
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Descrizione libro Springer Mrz 1999, 1999. Buch. Condizione libro: Neu. 23.4x15.6x cm. 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. 682 pp. Englisch. Codice libro della libreria 9780387947259

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6.

Jeff Harrison
Editore: Springer Mrz 1999 (1999)
ISBN 10: 0387947256 ISBN 13: 9780387947259
Nuovi Quantità: 1
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Agrios-Buch
(Bergisch Gladbach, Germania)
Valutazione libreria
[?]

Descrizione libro Springer Mrz 1999, 1999. Buch. Condizione libro: Neu. 23.4x15.6x cm. 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. 682 pp. Englisch. Codice libro della libreria 9780387947259

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West, Mike
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ISBN 10: 0387947256 ISBN 13: 9780387947259
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Descrizione libro Springer, 2016. Paperback. Condizione libro: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Codice libro della libreria ria9780387947259_lsuk

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Mike West
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Descrizione libro Springer-Verlag New York Inc., 1999. HRD. Condizione libro: New. New Book. Delivered from our US warehouse in 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice libro della libreria I1-9780387947259

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Jeff Harrison
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AHA-BUCH GmbH
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Descrizione libro Springer Mrz 1999, 1999. Buch. Condizione libro: Neu. 235x155x43 mm. 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. Codice libro della libreria 9780387947259

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Descrizione libro Condizione libro: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely. Codice libro della libreria NU-ING-00718925

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