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R-optimal designs for multi-factor models with heteroscedastic errors
Authors:Lei He  Rong-Xian Yue
Affiliation:1.Department of Mathematics,Shanghai Normal University,Shanghai,China;2.Scientific Computing Key Laboratory of Shanghai Universities,Shanghai,China
Abstract:
In this paper, we consider the R-optimal design problem for multi-factor regression models with heteroscedastic errors. It is shown that a R-optimal design for the heteroscedastic Kronecker product model is given by the product of the R-optimal designs for the marginal one-factor models. However, R-optimal designs for the additive models can be constructed from R-optimal designs for the one-factor models only if sufficient conditions are satisfied. Several examples are presented to illustrate and check optimal designs based on R-optimality criterion.
Keywords:
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