Statistical Methods for Forecasting

Johannes Ledolter

ISBN 10: 0471769878 / ISBN 13: 9780471769873

Editore: Wiley Sep 2005, 2005

Riguardo questo articolo

Neuware - The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.'This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!'-Journal of the Royal Statistical Society'A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates.'-ChoiceStatistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.

Codice articolo 9780471769873

Dati bibliografici

• Titolo: Statistical Methods for Forecasting
• Editore: Wiley Sep 2005
• Data di pubblicazione: 2005
• Lingua: Inglese
• ISBN 10: 0471769878
• ISBN 13: 9780471769873
• Rilegatura: Taschenbuch
• Edizione: seconda edizione
• Condizione: Neu
• Dimensioni: 229 L x 152 A x 28 P (millimetri) 229 millimetri di larghezza per 152 millimetri di altezza per 28 millimetri di profondità
• Peso: 766 grammi

Descrizione articolo

Riassunto

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.

"This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!"
-Journal of the Royal Statistical Society

"A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates."
-Choice

Statistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.

Informazioni sull'autore

BOVAS ABRAHAM, PhD, is Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo, Ontario, Canada. He is a Fellow of the American Statistical Association, and a member of the Statistical Society of Canada and the Royal Statistical Society. Dr. Abraham received his PhD in statistics from the University of Wisconsin?Madison.

JOHANNES LEDOLTER, PhD, is Associate Professor in both the Department of Statistics and Actuarial Science and the Department of Management Sciences at the University of Iowa. He is a Fellow of the American Statistical Association and a member of the International Statistical Institute. Dr. Ledolter is coauthor of Statistical Quality Control: Strategies and Tools for Continual Improvement and Achieving Quality Through Continual Improvement, both published by Wiley. He received his PhD in statistics from the University of Wisconsin?Madison.