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	Bayesian optimal blocking of factorial designs
	Ai, Mingyao ; Kang, Lulu ; Joseph, V. Roshan
	2009
关键词	Block design Bayesian method Combined wordlength pattern Minimum aberration MINIMUM ABERRATION BLOCKING 2(N-P) DESIGNS 2-LEVEL SCHEMES RESOLUTION
英文摘要	The presence of block effects makes the optimal selection of fractional factorial designs a difficult task. The existing frequentist methods try to combine treatment and block wordlength patterns and apply minimum aberration criterion to find the optimal design. However, ambiguities exist in combining the two wordlength patterns and therefore, the optimality of such designs can be challenged. Here we propose a Bayesian approach to overcome this problem. The main technique is to Postulate a model and a prior distribution to satisfy the common assumptions in blocking and then, to develop an optimal design criterion for the efficient estimation of treatment effects. We apply our method to develop regular, nonregular, and mixed-level blocked designs. Several examples are presented to illustrate the advantages of the proposed method. Published by Elsevier B.V; Statistics & Probability; SCI(E); 0; ARTICLE; 9; 3319-3328; 139
语种	英语
出处	SCI
出版者	journal of statistical planning and inference
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/157767]
专题	数学科学学院
推荐引用方式 GB/T 7714	Ai, Mingyao,Kang, Lulu,Joseph, V. Roshan. Bayesian optimal blocking of factorial designs. 2009-01-01.

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