Comparison of Bayes' and minimum variance unbiased estimators of reliability in the extreme value life testing model

dc.contributor.authorGodbold, James Homeren
dc.contributor.departmentStatisticsen
dc.date.accessioned2016-04-21T15:35:14Zen
dc.date.available2016-04-21T15:35:14Zen
dc.date.issued1970en
dc.description.abstractThe purpose of this study is to consider two different types of estimators for reliability using the extreme value distribution as the life-testing model. First the unbiased minimum variance estimator is derived. Then the Bayes' estimators for the uniform, exponential, and inverted gamma prior distributions are obtained, and these results are extended to a whole class of exponential failure models. Each of the Bayes' estimators is compared with the unbiased minimum variance estimator in a Monte Carlo simulation where it is shown that the Bayes' estimator has smaller squared error loss in each case. The problem of obtaining estimators with respect to an exponential type loss function is also considered. The difficulties in such an approach are demonstrated.en
dc.description.degreeMaster of Scienceen
dc.format.extentvii, 90 leavesen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/10919/70543en
dc.language.isoen_USen
dc.publisherVirginia Polytechnic Institute and State Universityen
dc.relation.isformatofOCLC# 20498659en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.lccLD5655.V855 1970.G62en
dc.subject.lcshBayesian statistical decision theoryen
dc.subject.lcshAnalysis of varianceen
dc.titleComparison of Bayes' and minimum variance unbiased estimators of reliability in the extreme value life testing modelen
dc.typeThesisen
dc.type.dcmitypeTexten
thesis.degree.disciplineStatisticsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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