D-Optimum Designs for Heteroscedastic Linear Models
作者:
A.C. Atkinson,
R.D. Cook,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1995)
卷期:
Volume 90,
issue 429
页码: 204-212
ISSN:0162-1459
年代: 1995
DOI:10.1080/01621459.1995.10476503
出版商: Taylor & Francis Group
关键词: Bayesian design;General equivalence theorem;Taguchi methods
数据来源: Taylor
摘要:
The methods of optimum experimental design are applied to models in which the variance, as well as the mean, is a parametric function of explanatory variables. Extensions to standard optimality theory lead to designs when the parameters of both the mean and the variance functions, or the parameters of only one function, are of interest. The theory also applies whether the mean and variance are functions of the same variables or of different variables, although the mathematical foundations differ. The example studied is a second-order two-factor response surface for the mean with a parametric nonlinear variance function. The theory is used both for constructing designs and for checking optimality. A major potential for application is to experimental design in off-line quality control.
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