Bayesian-inspired minimum aberration two- and four-level designs

V. Roshan Joseph, Mingyao Ai and C. F. Jeff Wu

Biometrika, 2009, vol. 96, issue 1, 95-106

Abstract: Motivated by a Bayesian framework, we propose a new minimum aberration-type criterion for designing experiments with two- and four-level factors. The Bayesian approach helps in overcoming the ad hoc nature of effect ordering in the existing minimum aberration-type criteria. The approach is also capable of distinguishing between qualitative and quantitative factors. Numerous examples are given to demonstrate its advantages. Copyright 2009, Oxford University Press.

Date: 2009
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