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Forecasting with Exponential Smoothing : The State Space Approach

Koehler, Anne B., Hyndman, Rob, Ord, J. Keith, Snyder, Ralph D.

Edit� par Springer Berlin / Heidelberg, 2008

ISBN 10 : 3540719164 ISBN 13 : 9783540719168

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Forecasting with Exponential Smoothing: The State Space Approach (Springer Series in Statistics)

Hyndman, Rob

Edit� par Springer, 2008

ISBN 10 : 3540719164 ISBN 13 : 9783540719168

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Forecasting with Exponential Smoothing : The State Space Approach

Hyndman, Rob; Koehler, Anne B.; Ord, J. Keith; Snyder, Ralph D.

Edit� par Springer, 2008

ISBN 10 : 3540719164 ISBN 13 : 9783540719168

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Forecasting with Exponential Smoothing: The State Space Approach (Springer Series in Statistics)

Hyndman, Rob

Edit� par Springer, 2008

ISBN 10 : 3540719164 ISBN 13 : 9783540719168

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Forecasting with Exponential Smoothing : The State Space Approach

Hyndman, Rob; Koehler, Anne B.; Ord, J. Keith; Snyder, Ralph D.

Edit� par Springer, 2008

ISBN 10 : 3540719164 ISBN 13 : 9783540719168

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Forecasting with Exponential Smoothing

Rob Hyndman

Edit� par Springer Berlin Heidelberg Jul 2008, 2008

ISBN 10 : 3540719164 ISBN 13 : 9783540719168

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and industry. However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. This book brings together all of the important new results on the state space framework for exponential smoothing. It will be of interest to people wanting to apply the methods in their own area of interest as well as for researchers wanting to take the ideas in new directions. Part 1 provides an introduction to exponential smoothing and the underlying models. The essential details are given in Part 2, which also provide links to the most important papers in the literature. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems. Applications to particular domains are discussed in Part 4. 380 pp. Englisch. N� de r�f. du vendeur 9783540719168

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Forecasting with Exponential Smoothing

Rob Hyndman|Anne B. Koehler|J. Keith Ord|Ralph D. Snyder

Edit� par Springer Berlin Heidelberg, 2008

ISBN 10 : 3540719164 ISBN 13 : 9783540719168

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Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides solid intellectual foundation for exponential smoothing methodsGives overview of current topics and develops new ideas that have not appeared in the academic literatureThe forecast package for R implements the methods described in . N� de r�f. du vendeur 4899314

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Forecasting with Exponential Smoothing : The State Space Approach

Rob Hyndman

Edit� par Springer Berlin Heidelberg, 2008

ISBN 10 : 3540719164 ISBN 13 : 9783540719168

Neuf Taschenbuch

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and industry. However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. This book brings together all of the important new results on the state space framework for exponential smoothing. It will be of interest to people wanting to apply the methods in their own area of interest as well as for researchers wanting to take the ideas in new directions. Part 1 provides an introduction to exponential smoothing and the underlying models. The essential details are given in Part 2, which also provide links to the most important papers in the literature. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems. Applications to particular domains are discussed in Part 4. N� de r�f. du vendeur 9783540719168