Forecasting with Exponential Smoothing
The State Space Approach
Authors: Hyndman, R., Koehler, A.B., Ord, J.K., Snyder, R.D.
Free Preview- Provides solid intellectual foundation for exponential smoothing methods
- Gives overview of current topics and develops new ideas that have not appeared in the academic literature
- The forecast package for R implements the methods described in the book
- Many graphics included
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- About this book
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Exponential smoothing methods have been around since the 1950s, and are the most popular forecasting methods used in business and industry. Recently, exponential smoothing has been revolutionized with the introduction of a complete modeling framework incorporating innovations state space models, likelihood calculation, prediction intervals and procedures for model selection. In this book, all of the important results for this framework are brought together in a coherent manner with consistent notation. In addition, many new results and extensions are introduced and several application areas are examined in detail.
Rob J. Hyndman is a Professor of Statistics and Director of the Business and Economic Forecasting Unit at Monash University, Australia. He is Editor-in-Chief of the International Journal of Forecasting, author of over 100 research papers in statistical science, and received the 2007 Moran medal from the Australian Academy of Science for his contributions to statistical research.
Anne B. Koehler is a Professor of Decision Sciences and the Panuska Professor of Business Administration at Miami University, Ohio. She has numerous publications, many of which are on forecasting models for seasonal time series and exponential smoothing methods.
J.Keith Ord is a Professor in the McDonough School of Business, Georgetown University, Washington DC. He has authored over 100 research papers in statistics and its applications and ten books including Kendall's Advanced Theory of Statistics.
Ralph D. Snyder is an Associate Professor in the Department of Econometrics and Business Statistics at Monash University, Australia. He has extensive publications on business forecasting and inventory management. He has played a leading role in the establishment of the class of innovations state space models for exponential smoothing.
- Table of contents (20 chapters)
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Basic Concepts
Pages 3-7
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Getting Started
Pages 9-29
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Linear Innovations State Space Models
Pages 33-51
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Nonlinear and Heteroscedastic Innovations State Space Models
Pages 53-66
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Estimation of Innovations State Space Models
Pages 67-74
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Table of contents (20 chapters)
- Download Preface 1 PDF (185.4 KB)
- Download Sample pages 1 PDF (312.1 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Forecasting with Exponential Smoothing
- Book Subtitle
- The State Space Approach
- Authors
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- Robin Hyndman
- Anne B. Koehler
- J. Keith Ord
- Ralph D. Snyder
- Series Title
- Springer Series in Statistics
- Copyright
- 2008
- Publisher
- Springer-Verlag Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
- eBook ISBN
- 978-3-540-71918-2
- DOI
- 10.1007/978-3-540-71918-2
- Softcover ISBN
- 978-3-540-71916-8
- Series ISSN
- 0172-7397
- Edition Number
- 1
- Number of Pages
- XIII, 362
- Topics
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