SAS for Forecasting Time Series, Third Edition

SAS for Forecasting Time Series, Third Edition

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To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject. With this third edition of SAS for Forecasting Time Series, intermediate-to-advanced SAS users—such as statisticians, economists, and data scientists—can now match the most sophisticated forecasting methods to the most current SAS applications.

Starting with fundamentals, this new edition presents methods for modeling both univariate and multivariate data taken over time. From the well-known ARIMA models to unobserved components, methods that span the range from simple to complex are discussed and illustrated. Many of the newer methods are variations on the basic ARIMA structures.

Completely updated, this new edition includes fresh, interesting business situations and data sets, and new sections on these up-to-date statistical methods:

  • ARIMA models
  • Vector autoregressive models
  • Exponential smoothing models
  • Unobserved component and state-space models
  • Seasonal adjustment
  • Spectral analysis

Focusing on application, this guide teaches a wide range of forecasting techniques by example. The examples provide the statistical underpinnings necessary to put the methods into practice. The following up-to-date SAS applications are covered in this edition:

  • The ARIMA procedure
  • The AUTOREG procedure
  • The VARMAX procedure
  • The ESM procedure
  • The UCM and SSM procedures
  • The X13 procedure
  • The SPECTRA procedure
  • SAS Forecast Studio

Each SAS application is presented with explanation of its strengths, weaknesses, and best uses. Even users of automated forecasting systems will benefit from this knowledge of what is done and why. Moreover, the accompanying examples can serve as templates that you easily adjust to fit your specific forecasting needs.

This book is part of the SAS Press program.

Product Details

ISBN-13: 9781629605449
Publisher: SAS Institute
Publication date: 03/14/2018
Sold by: Barnes & Noble
Format: NOOK Book
Pages: 384
Sales rank: 905,116
File size: 77 MB
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About the Author

John C. Brocklebank, PhD, is Executive Vice President, Global Hosting and US Professional Services, at SAS. Dr. Brocklebank brings more than 35 years of SAS programming and statistical experience to his leadership role at SAS. He holds 14 patents and directs the SAS Advanced Analytics Lab for State and Local Government, which devotes the resources of nearly 300 mostly doctoral-level SAS experts to devising technology solutions to critical state and local government issues. He also serves on the Board of Directors for the North Carolina State College of Sciences Foundation, where he advises the dean and college leaders on issues affecting the future direction of the college. In addition, he is a member of the Lipscomb University College of Computing and Technology Advancement Council and the Analytics Corporate Advisory Board, Analytics and Data Mining Programs, Spears School of Business at Oklahoma State University. Dr. Brocklebank holds an MS in biostatistics and in 1981 received a PhD in statistics and mathematics from North Carolina State University, where he now serves as a Physical and Mathematical Sciences Foundation board member and an adjunct professor of statistics.
David A. Dickey, PhD, is a William Neal Reynolds Distinguished Professor of Statistics at North Carolina State University, where he teaches graduate courses in statistical methods and time series. An accomplished SAS user since 1976, an award-winning teacher, and a prolific and highly cited author, he co-invented the famous Dickey-Fuller test used in SAS/ETS software. He is a fellow of the American Statistical Association, was a founding member of the NCSU Institute for Advanced Analytics, is a member of the Financial Math faculty, and fulfills an associate appointment in the Department of Agricultural and Resource Economics. Dr. Dickey holds an MS in mathematics from Miami University–Ohio, and in 1976 he received his PhD in statistics from Iowa State University.
Bong S. Choi, PhD, is a Senior Associate Analytical Consultant at SAS. He has worked on projects across a variety of industries, including health care, retail, and banking. A SAS certified advanced programmer, he has been a SAS user since 2011. Dr. Choi holds an MS in applied statistics from the University of Michigan at Ann Arbor and in 2016 received his PhD in statistics from North Carolina State University.

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