Forecasting with Exponential Smoothing (Paperback)
Rob Hyndman
Verkauft von AussieBookSeller, Truganina, VIC, Australien
AbeBooks-Verkäufer seit 22. Juni 2007
Neu - Softcover
Zustand: Neu
Anzahl: 1 verfügbar
In den Warenkorb legenVerkauft von AussieBookSeller, Truganina, VIC, Australien
AbeBooks-Verkäufer seit 22. Juni 2007
Zustand: Neu
Anzahl: 1 verfügbar
In den Warenkorb legenPaperback. 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. However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Bestandsnummer des Verkäufers 9783540719168
This book brings together all of the important new results on the state space framework for exponential smoothing. It gives an overview of current topics and develops new ideas that have not appeared in the academic literature.
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