An efficient screening method for computer experiments


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.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Computer Science
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in Technometrics on 7/12/13 available online:
Uncontrolled Keywords: Morris design,sensitivity analysis,variable selection,Modelling and Simulation,Statistics and Probability,Applied Mathematics
Publication ISSN: 1537-2723
Full Text Link: http://www.tand ... 99#.VW8UCEY9nRc
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2014
Published Online Date: 2013-12-07
Authors: Boukouvalas, Alexios
Gosling, John Paul
Maruri-Aguilar, Hugo



Version: Accepted Version

Export / Share Citation


Additional statistics for this record