Issues in the optimal design of computer simulation experiments

被引:20
|
作者
Mueller, Werner [1 ]
Stehlik, Milan [1 ]
机构
[1] Johannes Kepler Univ Linz, Dept Appl Stat, A-4040 Linz, Austria
关键词
optimum experimental design; computer experiment; D-optimality; efficiency; equidistant design; parameterized covariance functions; Smit's paradox; SPATIAL SAMPLING DESIGN; MAXIMUM-LIKELIHOOD-ESTIMATION; PARAMETER-ESTIMATION; PREDICTION; MODEL; INFORMATION; ERROR;
D O I
10.1002/asmb.740
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Output front Computer simulation experiments is often approximated as realizations of correlated random fields. Consequently, the corresponding optimal design questions must cope with the existence and detection of an error con-elation structure, issues largely unaccounted for by traditional optimal design theory. Unfortunately, many of the nice features of well-established design techniques, such as additivity of the information matrix, convexity of design criteria, etc., do not carry over to the setting of interest. This may lead to unexpected, counterintuitive, even paradoxical effects in the design as well as the analysis stage of computer Simulation experiments. In this paper we intend to give an overview and some simple but illuminating examples of this behaviour. Copyright (C) 2009 John Wiley & Sons, Ltd.
引用
收藏
页码:163 / 177
页数:15
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