Optimal minimax designs over a prespecified interval in a heteroscedastic polynomial model

Ray Bing Chen; Weng Kee Wong; Kun Yu Li

doi:10.1016/j.spl.2008.01.059

Optimal minimax designs over a prespecified interval in a heteroscedastic polynomial model

Ray Bing Chen, Weng Kee Wong, Kun Yu Li

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

Abstract

Minimax optimal designs can be useful for estimating response surface but they are notoriously difficult to study analytically. We provide the formulae for three types of minimax optimal designs over a user-specified region. We focus on polynomial models with various types of heteroscedastic errors but the design strategy is applicable to other types of linear models and optimality criteria. Relationships among the three types of minimax optimal designs are discussed.

Original language	English
Pages (from-to)	1914-1921
Number of pages	8
Journal	Statistics and Probability Letters
Volume	78
Issue number	13
DOIs	https://doi.org/10.1016/j.spl.2008.01.059
Publication status	Published - 2008 Sept 15

All Science Journal Classification (ASJC) codes

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/j.spl.2008.01.059

Cite this

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abstract = "Minimax optimal designs can be useful for estimating response surface but they are notoriously difficult to study analytically. We provide the formulae for three types of minimax optimal designs over a user-specified region. We focus on polynomial models with various types of heteroscedastic errors but the design strategy is applicable to other types of linear models and optimality criteria. Relationships among the three types of minimax optimal designs are discussed.",

author = "Chen, {Ray Bing} and Wong, {Weng Kee} and Li, {Kun Yu}",

note = "Funding Information: The research of Chen is partially supported by grants from the National Science Council in Taiwan, R.O.C. The research of Wong is partially supported by NIH grants 30841, 31068 and R01GM072876. ",

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AU - Wong, Weng Kee

AU - Li, Kun Yu

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N2 - Minimax optimal designs can be useful for estimating response surface but they are notoriously difficult to study analytically. We provide the formulae for three types of minimax optimal designs over a user-specified region. We focus on polynomial models with various types of heteroscedastic errors but the design strategy is applicable to other types of linear models and optimality criteria. Relationships among the three types of minimax optimal designs are discussed.

AB - Minimax optimal designs can be useful for estimating response surface but they are notoriously difficult to study analytically. We provide the formulae for three types of minimax optimal designs over a user-specified region. We focus on polynomial models with various types of heteroscedastic errors but the design strategy is applicable to other types of linear models and optimality criteria. Relationships among the three types of minimax optimal designs are discussed.

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JO - Statistics and Probability Letters

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ER -

Optimal minimax designs over a prespecified interval in a heteroscedastic polynomial model

Abstract

All Science Journal Classification (ASJC) codes

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