Browsing by Subject "Statistical tolerance regions"
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Item Accelerated life testing with several type II censored samples(1989-08) McCoun, Kelly Lynn; Kolarik, William J.; Davenport, James M.; Duran, Benjamin S.; Lewis, Truman O.; Ghiassi, Hossein MansouriThe asymptotic normality of the maximum likelihood estimator for a likelihood function based on several independent Type II censored samples is established. Examples from the accelerated Hfe class of models are considered with regard to this result. This extends previous work for the single sample case. Conditional confidence interval estimation is discussed for the parameters in the Arrhenius and Eyring models based on data from several Type II censored samples. Conditional confidence interval estimates for the average life of a component under user-specified stress, the acceleration factor or the factor which expresses how many times longer a component should last at one stress relative to another, and the 7th quantile of the failure time distribution of a component under user-specified stress are also provided. Approximate confidence intervals for these parameters are given for comparison with the conditional confidence intervals.Item Covariance estimation based on asymptotic normal estimating function(Texas Tech University, 1998-12) Hwang, Ming-WoeiSurvival analysis is the analysis of data that corresponds to the time from a welldefined origin of time until the occurrence of some particular event or end point. In medical research, the origin of fime could be the time of birth, or the recruitment of an individual into an experiment study, such as clinical trial to compare two or more treatments. If the end point is the death of a patient, the resulting data are literally survival times. The two-sample accelerated life model has been a general model for comparing censored survival times from two groups. This model assumes that the survival time of an individual in one group is distributed as a multiple of the survival time of an individual in the other group. Therefore, the probability of an individual on the new treatment surviving over time is the probability of an individual under the standard treatment surviving over time 01, where ^ is an unknown positive scale.