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dc.contributor.authorHuang, Wan-yi
dc.date.accessioned2015-09-22T13:09:55Z
dc.date.available2015-09-22T13:09:55Z
dc.identifier.urihttp://hdl.handle.net/10464/7230
dc.description.abstractAccelerated life testing (ALT) is widely used to obtain reliability information about a product within a limited time frame. The Cox s proportional hazards (PH) model is often utilized for reliability prediction. My master thesis research focuses on designing accelerated life testing experiments for reliability estimation. We consider multiple step-stress ALT plans with censoring. The optimal stress levels and times of changing the stress levels are investigated. We discuss the optimal designs under three optimality criteria. They are D-, A- and Q-optimal designs. We note that the classical designs are optimal only if the model assumed is correct. Due to the nature of prediction made from ALT experimental data, attained under the stress levels higher than the normal condition, extrapolation is encountered. In such case, the assumed model cannot be tested. Therefore, for possible imprecision in the assumed PH model, the method of construction for robust designs is also explored.en_US
dc.language.isoengen_US
dc.publisherBrock Universityen_US
dc.subjectStep-stress accelerated life testen_US
dc.subjectCox's proportional hazards modelen_US
dc.subjectRobust designen_US
dc.subjectMaximum likelihood estimationen_US
dc.subjectReliability estimationen_US
dc.titleOptimal and Robust Designs of Step-stress Accelerated Life Testing Experiments for Proportional Hazards Modelsen_US
dc.typeElectronic Thesis or Dissertationen_US
dc.degree.nameM.Sc. Mathematics and Statisticsen_US
dc.degree.levelMastersen_US
dc.contributor.departmentDepartment of Mathematicsen_US
dc.degree.disciplineFaculty of Mathematics and Scienceen_US
refterms.dateFOA2021-07-31T02:02:08Z


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