Screening the Input Variables to a Computer Model Via Analysis of Variance and Visualization

Matthias Schonlau () and William J. Welch ()
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Matthias Schonlau: RAND Corporation
William J. Welch: University of British Columbia, Department of Statistics

Chapter 14 in Screening, 2006, pp 308-327 from Springer

Abstract: Abstract A nexperiment involving a complex computer model or code may have tens or even hundreds of input variables and, hence, the identification of the more important variables (screening) is often crucial. Methods are described for decomposing a complex input—output relationship into effects. Effects are more easily understood because each is due to only one or a small number of input variables. They can be assessed for importance either visually or via a functional analysis of variance. Effects are estimated from flexible approximations to the input—output relationships of the computer model. This allows complex nonlinear and interaction relationships to be identified. The methodology is demonstrated on a computer model of the relationship between environmental policy and the world economy.

Keywords: Marginal Effect; Computer Experiment; Human Development Index; Corrected Effect; Output Relationship (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-0-387-28014-1_14

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DOI: 10.1007/0-387-28014-6_14

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