Browsing by Subject "Confidence intervals"
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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 Confidence intervals for computable general equilibrium models(2003) Tuladhar, Sugandha Dhar; Wilcoxen, Peter J.Computable general equilibrium (CGE) models have expanded from being a simple theoretical tool to a widely accepted policy evaluation tool. Despite recognizing that model parameters involve uncertainty, virtually all modelers report their results without confidence intervals. This obscures the uncertainty inherent in the models and gives the impression that the results are far more certain than they actually are. CGE models with calibrated parameters and econometric CGE models using only the mean value of the parameters share a common flaw: their results are point estimates only, with no indication of the range of possible variation. A better analysis would include confidence intervals that communicate the underlying uncertainty. This would allow the policy makers to understand the precision of the results. In this dissertation a tractable formal technique for calculating confidence intervals is presented. The results from this approach are compared with sensitivity analysis, an alternative method sometimes used for assessing uncertainty. It is shown for the models presented that sensitivity analysis can produce misleading results and that the confidence intervals are feasible to compute and qualitatively superior. Next, the technique is applied to an econometric intertemporal general equilibrium model of the US economy to examine a current policy issue. The strong form of the double dividend hypothesis, which asserts that revenue-neutral substitution of an environmental tax for a distortionary income tax can improve welfare, is tested. The intertemporal equivalent variation (EV) for the policy is calculated. Unlike other studies, however, the 95 percent confidence interval for the EV is presented. The mean EV is slightly negative but the confidence interval is large and includes zero, so the model neither supports nor rejects the double dividend hypothesis. In addition, the short-run and the long-run intratemporal EV is calculated and compared to the intertemporal EV. The result implies that the long-run result supports the double dividend hypothesis even though the short-run does not. Finally, I present a detailed analysis of the general equilibrium effects that yield these distinct and contradictory results. In sum, this dissertation provides an econometric view of CGE modeling and statistical testing of CGE results that is acceptable to econometricians. It attempts to answer criticisms of CGE modeling and the wider challenge to empiricism in economics (Whalley, 1985).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.Item On nonparametric confidence intervals for scale parameters(Texas Tech University, 2001-05) Martinez, Ruby R.In this thesis, the main focus is on nonparametric confidence intervals for scale parameters. The general technique of forming confidence intervals will be discussed. We consider testing a particular hypothesis using an appropriate test statistic. The critical region will be identified and those values of the parameter for which the null hypothesis is accepted will be used to yield a confidence interval. This is a general procedure for determining confidence intervals, and more details will be given in ensuing chapters. This is a general procedure for determining confidence intervals.