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Applied data mining for forecasting using SAS /
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...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Autor Corporativo: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cary, N.C. :
SAS Institute,
2012.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
| Sumario: | 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. |
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| Descripción Física: | 1 online resource (x, 324 pages) : illustrations |
| Bibliografía: | Includes bibliographical references (pages 313-316) and index. |
| ISBN: | 9781612900933 1612900933 1607646625 9781607646624 |