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A Discussion of Alternative Ways of Modeling and Interpreting Mixture Data

Summary: [This abstract is based on the authors' abstract.]Models for regression where some of the variables are mixture components are discussed and compared. The model chosen can affect parameter interpretation. Recommendations and precautions are considered when using some regression procedures with standard statistical software packages. Combinations of variables that will provide data with good predictive properties are also discussed. An example from the carbon industry illustrates the methods.

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  • Topics: Statistical Process Control (SPC)
  • Keywords: ARL contour plots,Mixture variables,Model discrimination,Process centering,Validation,Variable selection
  • Author: Bjorkestol, Kirsten; Naes, Tormod
  • Journal: Quality Engineering