A useful empirical Bayesian method to analyse industrial data from saturated factorial designs

The use of saturated two-level designs is very popular, especially in industrial applications where the cost of experiments is too high. Standard classical approaches are not appropriate to analyze data from saturated designs, since we could only get the estimates of the main factor effects and we w...

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Bibliographic Details
Published inInternational journal of industrial engineering computations Vol. 4; no. 3; p. 337
Main Authors Baba, Marta Yukie, Achcar, Jorge Alberto, Moala, Fernando Antonio, Oikawa, Sergio Minoru, Piratelli, Claudio Luis
Format Journal Article
LanguageEnglish
Published Growing Science 2013
Subjects
Bayesian analysis
Degrees of freedom
Empirical analysis
Empirical Bayesian methods
Error analysis
Estimates
Mathematical analysis
Plackett-Burman designs
Reproduction
Saturated designs
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Summary:The use of saturated two-level designs is very popular, especially in industrial applications where the cost of experiments is too high. Standard classical approaches are not appropriate to analyze data from saturated designs, since we could only get the estimates of the main factor effects and we would not have degrees of freedom to estimate the variance of the error. In this paper, we propose the use of empirical Bayesian procedures to get inferences for data obtained from saturated designs. The proposed methodology is illustrated assuming a simulated data set. [copy 2013 Growing Science Ltd. All rights reserved
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ISSN:1923-2926
1923-2934
DOI:10.5267/j.ijiec.2013.04.001