dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorTsunemi, Miriam Harumi
dc.creatorCampos, Thiago Feitosa
dc.creatorEsteves, Luís Gustavo
dc.creatorLeite, José Galvão
dc.creatorWechsler, Sergio
dc.date2014-05-27T11:26:57Z
dc.date2016-10-25T18:38:16Z
dc.date2014-05-27T11:26:57Z
dc.date2016-10-25T18:38:16Z
dc.date2012-09-01
dc.date.accessioned2017-04-06T02:00:31Z
dc.date.available2017-04-06T02:00:31Z
dc.identifierJournal of Statistical Planning and Inference, v. 142, n. 9, p. 2701-2709, 2012.
dc.identifier0378-3758
dc.identifierhttp://hdl.handle.net/11449/73527
dc.identifierhttp://acervodigital.unesp.br/handle/11449/73527
dc.identifier10.1016/j.jspi.2012.03.021
dc.identifier2-s2.0-84860888754
dc.identifierhttp://dx.doi.org/10.1016/j.jspi.2012.03.021
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/894330
dc.descriptionA Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual quality deterioration and allows the incorporation of an expert's opinion on the production process. Based on the number of inspections to be carried out until a defective item is found, the Bayesian operation for the distribution function that represents the increasing sequence of defective fractions during a cycle considering a mixture of Dirichlet processes as prior distribution is performed. Bayes estimates for relevant quantities are also obtained. © 2012 Elsevier B.V.
dc.languageeng
dc.relationJournal of Statistical Planning and Inference
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBayesian estimation
dc.subjectBayesian operation
dc.subjectContinued quality deterioration
dc.subjectMixture of Dirichlet processes
dc.subjectTaguchi's procedure for attributes
dc.titleA Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes
dc.typeOtro


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