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Applied Data Mining for Forecasting Using SAS - Tim Rey

Applied Data Mining for Forecasting Using SAS

By: Tim Rey, Ph.D. Arthur Kordon, Ph.D. Chip Wells

Paperback | 31 July 2012

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Applied Data Mining for Forecasting Using SAS, by Tim Rey, Arthur Kordon, and Chip Wells, introduces and describes approaches for mining large time series data sets. Written for forecasting practitioners, engineers, statisticians, and economists, the book details how to select useful candidate input variables for time series regression models in environments when the number of candidates is large, and identifies the correlation structure between selected candidate inputs and the forecast variable. This book is essential for forecasting practitioners who need to understand the practical issues involved in applied forecasting in a business setting. Through numerous real-world examples, the authors demonstrate how to effectively use SAS software to meet their industrial forecasting needs.
Industry Reviews
"I believe this is an excellent book for frontier practitioners and researchers, especially in the forecasting and data mining fields. Leveraging data mining techniques in an era where economic data and industry trend data are ample and readily available for building casual-effect forecasting models is a very promising endeavor. With a good causal-effect predictive model built through this approach, businesses would know what external and internal factors are truly driving effects and scenario-based forecasts and hence various contingency plans could be made in a timely fashion. I applaud the great effort by the authors." -- Jerry Z. Shan, Principal Scientist, HP Labs "Hewlett-Packard Company"

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