Maximum projection designs for computer experiments
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TL;DR: In this article, the authors proposed a method to maximize space-filling properties on projections to all subsets of factors, which can be computed at no more cost than a design criterion that ignores projection properties.
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Abstract: SUMMARY Space-filling properties are important in designing computer experiments. The traditional maximinandminimaxdistancedesignsconsideronlyspace-fillinginthefull-dimensionalspace; thiscanresultinpoorprojectionsontolower-dimensionalspaces,whichisundesirablewhenonly af ew factors are active. Restricting maximin distance design to the class of Latin hypercubes can improveone-dimensionalprojectionsbutcannotguaranteegoodspace-fillingpropertiesinlarger subspaces. We propose designs that maximize space-filling properties on projections to all subsets of factors. We call our designs maximum projection designs. Our design criterion can be computed at no more cost than a design criterion that ignores projection properties.
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Design and analysis of computer experiments
Sonja Kuhnt,David M. Steinberg +1 more
TL;DR: The included papers present an interesting mixture of recent developments in the field as they cover fundamental research on the design of experiments, models and analysis methods as well as more applied research connected to real-life applications.
Design and Analysis of Computer Experiments
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- 07 Mar 2014
TL;DR: It is concluded that the strategy as proposed by Sacks and coworkers is not suited for implementation in a design optimization tool, mainly because of two reasons: maximum likelihood parameter estimation is computationally expensive and not straightforward, while the quality of the parameter estimations is questionable.