Bayesian Forecasting and Dynamic Models

Name: Bayesian Forecasting and Dynamic Models
Brand: Springer Nature B.V.
SKU: 9781475770971
Price: 1270 CZK
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Autor: Mike West, Jeff Harrison

Jazyk:

Vazba: Brožovaná

Vydavatel: Springer Nature B.V.

Dostupnost: Skladem u dodavatele

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This text is concerned with Bayesian learning, inference and forecasting in dynamic environments. We...

Informace o knize

Autor

Mike West, Jeff Harrison

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2013

Stránek

700

EAN

9781475770971

ISBN

1475770979

Enbook ID

50419832

Vydavatel

Springer Nature B.V.

Hmotnost

966

Rozměry

156 x 234 x 36

Kompletní popis

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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