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Status已发表Published
TitleExperimental designs for computer experiments and for industrial experiments with model unknown
Creator
Date Issued2002
Source PublicationJournal of the Korean Statistical Society
ISSN1226-3192
Volume31Issue:3Pages:277-299
Abstract

Most statistical designs, such as orthogonal designs and optimal designs, are based on a specific statistical model. It is very often that the experimenter does not completely know the underlying model between the response and the factors. In computer experiments, the underlying model is known, but too complicated. In this case we can treat the model as a black box, or model to be unknown. Both cases need a space filling design. The uniform design is one of space filling designs and seeks experimental points to be uniformly scattered on the domain. The uniform design can be used for computer experiments and also for industrial experiments when the underlying model is unknown. In this paper we shall introduce the theory and method of the uniform design and related data analysis and modelling methods. Applications of the uniform design to industry and other areas are discussed.

Keywordcomputer experiments experiment with mixtures factorial design uniform design
URLView source
Language英语English
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Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/5172
CollectionResearch outside affiliated institution
Affiliation
Department of Mathematics, Hong Kong Baptist University, Hong Kong, China
Recommended Citation
GB/T 7714
Fang, Kaitai. Experimental designs for computer experiments and for industrial experiments with model unknown[J]. Journal of the Korean Statistical Society, 2002, 31(3): 277-299.
APA Fang, Kaitai. (2002). Experimental designs for computer experiments and for industrial experiments with model unknown. Journal of the Korean Statistical Society, 31(3), 277-299.
MLA Fang, Kaitai."Experimental designs for computer experiments and for industrial experiments with model unknown". Journal of the Korean Statistical Society 31.3(2002): 277-299.
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