dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorYukie Baba, Marta
dc.creatorAlberto Achcar, Jorge
dc.creatorAntonio Moala, Fernando
dc.creatorMinoru Oikawa, Sergio
dc.creatorLuis Piratelli, Claudio
dc.date2014-05-27T11:29:28Z
dc.date2016-10-25T18:48:19Z
dc.date2014-05-27T11:29:28Z
dc.date2016-10-25T18:48:19Z
dc.date2013-05-07
dc.date.accessioned2017-04-06T02:23:36Z
dc.date.available2017-04-06T02:23:36Z
dc.identifierInternational Journal of Industrial Engineering Computations, v. 4, n. 3, p. 337-344, 2013.
dc.identifier1923-2926
dc.identifier1923-2934
dc.identifierhttp://hdl.handle.net/11449/75365
dc.identifierhttp://acervodigital.unesp.br/handle/11449/75365
dc.identifier10.5267/j.ijiec.2013.04.001
dc.identifier2-s2.0-84877005337.pdf
dc.identifier2-s2.0-84877005337
dc.identifierhttp://dx.doi.org/10.5267/j.ijiec.2013.04.001
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/896111
dc.descriptionThe 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. © 2013 Growing Science Ltd. All rights reserved.
dc.languageeng
dc.relationInternational Journal of Industrial Engineering Computations
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectEmpirical bayesian methods
dc.subjectPlackett-burman designs
dc.subjectSaturated designs
dc.titleA useful empirical bayesian method to analyse industrial data from saturated factorial designs
dc.typeOtro


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