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Forecasting with Exponential Smoothing

The State Space Approach

  • Rob Hyndman
  • Anne Koehler
  • Keith Ord
  • Ralph Snyder

Part of the Springer Series in Statistics book series (SSS)

Table of contents

About this book

Introduction

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.

Keywords

Likelihood Stochastic model Stochastic models exponential smoothing innovation models inventory control modeling state space models supply chain time series

Authors and affiliations

  • Rob Hyndman
    • 1
  • Anne Koehler
    • 2
  • Keith Ord
    • 3
  • Ralph Snyder
    • 1
  1. 1.Department of Econometrics & Business StatisticsMonash UniversityClaytonAustralia
  2. 2.Department of Decision Sciences & Management Information SystemsMiami UniversityOxfordUSA
  3. 3.McDonough School of BusinessGeorgetown UniversityWashington DCUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-71918-2
  • Copyright Information Springer Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-540-71916-8
  • Online ISBN 978-3-540-71918-2
  • Series Print ISSN 0172-7397
  • Buy this book on publisher's site