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The Resource Applied Data Mining for Forecasting Using SAS(R), (electronic resource)

Applied Data Mining for Forecasting Using SAS(R), (electronic resource)

Label
Applied Data Mining for Forecasting Using SAS(R)
Title
Applied Data Mining for Forecasting Using SAS(R)
Creator
Contributor
Subject
Language
eng
Summary
  • Annotation
  • Annotation
  • Annotation:
Cataloging source
BIP US
http://library.link/vocab/creatorName
Rey, Tim
http://library.link/vocab/relatedWorkOrContributorName
  • Kordon, Arthur
  • Wells, Chip
Summary expansion
  • Applied Data Mining for Forecasting, 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
  • Applied Data Mining for Forecasting, 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
  • 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
Label
Applied Data Mining for Forecasting Using SAS(R), (electronic resource)
Instantiates
Publication
Control code
OCM1bookssj0000775652
Dimensions
unknown
Isbn
9781612900933
http://library.link/vocab/ext/overdrive/overdriveId
9781612900933
Specific material designation
remote
System control number
(WaSeSS)bookssj0000775652
Label
Applied Data Mining for Forecasting Using SAS(R), (electronic resource)
Publication
Control code
OCM1bookssj0000775652
Dimensions
unknown
Isbn
9781612900933
http://library.link/vocab/ext/overdrive/overdriveId
9781612900933
Specific material designation
remote
System control number
(WaSeSS)bookssj0000775652

Library Locations

    • Thomas Jefferson LibraryBorrow it
      1 University Blvd, St. Louis, MO, 63121, US
      38.710138 -90.311107
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