Applied Data Mining for Forecasting Using SAS

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...

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Detalles Bibliográficos
Autor Corporativo: SAS Institute (-)
Otros Autores: Rey, Tim Author (author), Kordon,Arthur Contributor (contributor), Wells,Chip Contributor
Formato: Libro electrónico
Idioma:Inglés
Publicado: [Place of publication not identified] SAS Institute 2012
Edición:1st edition
Materias:
SAS (Computer file)
Information Technology > General and Others
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628582706719
Tabla de Contenidos:
  • Why industry needs data mining for forecasting
  • Data mining for forecasting work process
  • Data mining for forecasting infrastructure
  • Issues with data mining for forecasting application
  • Data collection
  • Data preparation
  • A practitioner's guide to DMM methods for forecasting
  • Model building : ARMA models
  • Model building : ARIMAX or dynamic regression modes
  • Model building : further modeling topics
  • Model building : alternative modeling approaches
  • An example of data mining for forecasting.

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