Bayesian minimum aberration mixed-level split-plot designs

Hui Li, Min-Qian Liu and Jinyu Yang ()
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Hui Li: Nankai University
Min-Qian Liu: Nankai University
Jinyu Yang: Nankai University

Metrika: International Journal for Theoretical and Applied Statistics, 2024, vol. 87, issue 7, No 5, 889-906

Abstract: Abstract Many industrial experiments involve factors with levels more difficult to change or control than others, which leads to the development of two-level fractional factorial split-plot (FFSP) designs. Recently, mixed-level FFSP designs were proposed due to the requirement of different-level factors. In this paper, we generalize the Bayesian optimal criterion for mixed two- and four-level FFSP designs, and then provide Bayesian minimum aberration (MA) criterion to rank FFSP designs. Bayesian MA criterion can give a natural ordering for the effects involving two-level factors and three components of a four-level factor. We also discuss the relationship between the Bayesian optimal and Bayesian MA criteria. Furthermore, we consider the designs with both qualitative and quantitative factors.

Keywords: Fractional factorial; Minimum aberration; Mixed-level design; Split-plot design; Primary 62K15; Secondary 62K05 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s00184-023-00937-x

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