An efficient screening method for computer experiments

Alexios Boukouvalas*, John Paul Gosling, Hugo Maruri-Aguilar

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review


    Computer simulators of real-world processes are often computationally expensive and require many inputs. The problem of the computational expense can be handled using emulation technology; however, highly multidimensional input spaces may require more simulator runs to train and validate the emulator. We aim to reduce the dimensionality of the problem by screening the simulators inputs for nonlinear effects on the output rather than distinguishing between negligible and active effects. Our proposed method is built upon the elementary effects (EE) method for screening and uses a threshold value to separate the inputs with linear and nonlinear effects. The technique is simple to implement and acts in a sequential way to keep the number of simulator runs down to a minimum, while identifying the inputs that have nonlinear effects. The algorithm is applied on a set of simulated examples and a rabies disease simulator where we observe run savings ranging between 28% and 63% compared with the batch EE method. Supplementary materials for this article are available online.

    Original languageEnglish
    Pages (from-to)422-431
    Number of pages10
    Issue number4
    Early online date7 Dec 2013
    Publication statusPublished - 2014

    Bibliographical note

    This is an Accepted Manuscript of an article published by Taylor & Francis in Technometrics on 7/12/13 available online:


    • Morris design
    • sensitivity analysis
    • variable selection


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