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

In: Screening

Author

Listed:
  • Matthias Schonlau

    (RAND Corporation)

  • William J. Welch

    (University of British Columbia, Department of Statistics)

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.

Suggested Citation

  • Matthias Schonlau & William J. Welch, 2006. "Screening the Input Variables to a Computer Model Via Analysis of Variance and Visualization," Springer Books, in: Angela Dean & Susan Lewis (ed.), Screening, chapter 14, pages 308-327, Springer.
    • Handle: RePEc:spr:sprchp:978-0-387-28014-1_14
    DOI: 10.1007/0-387-28014-6_14
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