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Brocklebank J.C. et al. SAS for Forecasting Time Series

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Brocklebank J.C. et al. SAS for Forecasting Time Series
3rd ed. — SAS Institute, 2018. — 384 p. — ISBN: 9781629605463.
John C. Brocklebank , Ph.D. David A. Dickey , Ph.D. Bong Choi
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.
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