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Non-collapsing space-filling designs for bounded nonrectangular regions

Non-collapsing space-filling designs for bounded nonrectangular regions
Non-collapsing space-filling designs for bounded nonrectangular regions
Many researchers use computer simulators as experimental tools, especially when physical experiments are infeasible. When computer codes are computationally intensive, nonparametric predictors can be fitted to training data for detailed exploration of the input–output relationship. The accuracy of such flexible predictors is enhanced by taking training inputs to be “space-filling.” If there are inputs that have little or no effect on the response, it is desirable that the design be “noncollapsing” in the sense of having space-filling lower dimensional projections. This article describes an algorithm for constructing noncollapsing space-filling designs for bounded input regions that are of possibly high dimension. Online supplementary materials provide the code for the algorithm, examples of its use, and show its performance in multiple settings
0040-1706
169-178
Draguljic, Danel
258f315b-d392-4929-adeb-2c629bad68c4
Dean, Angela M.
9c90540a-cdf4-44ce-9d34-6b7b495a1ea3
Santner, Thomas J.
25c0e9d6-daa2-4757-bee2-a714805eb67c
Draguljic, Danel
258f315b-d392-4929-adeb-2c629bad68c4
Dean, Angela M.
9c90540a-cdf4-44ce-9d34-6b7b495a1ea3
Santner, Thomas J.
25c0e9d6-daa2-4757-bee2-a714805eb67c

Draguljic, Danel, Dean, Angela M. and Santner, Thomas J. (2012) Non-collapsing space-filling designs for bounded nonrectangular regions. Technometrics, 54 (2), 169-178. (doi:10.1080/00401706.2012.676951).

Record type: Article

Abstract

Many researchers use computer simulators as experimental tools, especially when physical experiments are infeasible. When computer codes are computationally intensive, nonparametric predictors can be fitted to training data for detailed exploration of the input–output relationship. The accuracy of such flexible predictors is enhanced by taking training inputs to be “space-filling.” If there are inputs that have little or no effect on the response, it is desirable that the design be “noncollapsing” in the sense of having space-filling lower dimensional projections. This article describes an algorithm for constructing noncollapsing space-filling designs for bounded input regions that are of possibly high dimension. Online supplementary materials provide the code for the algorithm, examples of its use, and show its performance in multiple settings

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More information

Published date: 25 May 2012
Organisations: Statistics, Statistical Sciences Research Institute

Identifiers

Local EPrints ID: 339790
URI: http://eprints.soton.ac.uk/id/eprint/339790
ISSN: 0040-1706
PURE UUID: f8576d19-7404-4779-baf9-5d4f2dad135f

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Date deposited: 30 May 2012 14:14
Last modified: 14 Mar 2024 11:15

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Contributors

Author: Danel Draguljic
Author: Angela M. Dean
Author: Thomas J. Santner

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