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Add to basketSoftcover. 251 S. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. 9780387772370 Sprache: Englisch Gewicht in Gramm: 550.
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Published by Springer-Verlag New York Inc., New York, NY, 2009
ISBN 10: 0387772375 ISBN 13: 9780387772370
Language: English
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condition: new. Paperback. State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed. State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Condition: New. pp. 268.
Published by Springer New York Jun 2009, 2009
ISBN 10: 0387772375 ISBN 13: 9780387772370
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware - State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.
Published by Springer-Verlag New York Inc., New York, NY, 2009
ISBN 10: 0387772375 ISBN 13: 9780387772370
Language: English
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Add to basketPaperback. Condition: new. Paperback. State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed. State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Published by Springer-Verlag New York Inc., 2009
ISBN 10: 0387772375 ISBN 13: 9780387772370
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 433.
Seller: moluna, Greven, Germany
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Fully worked-out examples in the freely available statistical software R Guides the reader in a friendly way from the basics of the Bayesian approach to its practical application to time series analysis Coverage includes advanced Bayesian c.
Seller: Majestic Books, Hounslow, United Kingdom
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Add to basketCondition: New. Print on Demand pp. 268 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
Seller: Biblios, Frankfurt am main, HESSE, Germany
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Add to basketCondition: New. PRINT ON DEMAND pp. 268.