期刊
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
卷 136, 期 3, 页码 1103-1119出版社
ELSEVIER
DOI: 10.1016/j.jspi.2004.08.007
关键词
alias matrix; entropy criterion; Latin hypercube designs; Lattice designs; maximin designs; mean squared error criterion; random field regression; rotation designs
For many complex processes laboratory experimentation is too expensive or too time-consuming to be carried out. A practical alternative is to simulate these phenomena by a computer code. This article considers the choice of an experimental design for computer experiments. We illustrate some drawbacks to criteria that have been proposed and suggest an alternative, based on the Bayesian interpretation of the alias matrix in Draper and Guttman (Ann. Inst. Statist. Math. 44 (1992) 659). Then we compare different design criteria by studying how they rate a variety of candidate designs for computer experiments such as Latin hypercube plans, U-designs, lattice designs and rotation designs. (c) 2004 Elsevier B.V. All rights reserved.
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