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Synopsis
Explains and demonstrates through examples how you can use SAS for time series analysis. It offers modern procedures for forecasting, seasonal adjustments, and decomposition of time series that can be used without involved statistical reasoning.
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About the Author
Anders Milhoj is Associate Professor in the Department of Economics at the University of Copenhagen, where he conducts research and lectures on applied statistics topics including survey sampling, regression analysis, time series analysis, and factor analysis. A SAS user since 1984, he employs a variety of SAS procedures in his work, such as SAS/STAT, SAS/IML, SAS/ETS, and SAS/OR. He holds university degrees in statistics and mathematics as well as a Ph.D. in statistics, all from the University of Copenhagen.
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