Case Study: Compressive Strength of Concrete Mixtures

Max Kuhn and Kjell Johnson
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Max Kuhn: Pfizer Global Research and Development, Division of Nonclinical Statistics
Kjell Johnson: Arbor Analytics

Chapter Chapter 10 in Applied Predictive Modeling, 2013, pp 225-243 from Springer

Abstract: Abstract The data set used in Chapters 6-9 to illustrate the model building process was based on observational data: the samples were selected from a predefined population and the predictors and response were observed. The case study in the chapter is used to explain the model building process for data that emanate from a designed experiment. In a designed experiment, the predictors and their desired values are prespecified. The specific combinations of the predictor values are also prespecified, which determine the samples that will be collected for the data set. The experiment is then conducted and the response is observed. In the context model building for a designed experiment we present a strategy (Section 10.1), recommendations for evaluating model performance (Section 10.2), an approach for identifying predictor combinations that produce an optimal response (Section 10.3), and syntax for building and evaluating models for this illustration (Section 10.4).

Keywords: Compressive Strength; Search Procedure; Desirability Function; Multivariate Adaptive Regression Spline; Mixture Proportion (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-6849-3_10

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DOI: 10.1007/978-1-4614-6849-3_10

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