الفهرس 
Title : On the Mixture and Additive Models of Flexible Weibull Extension and Burr XII Distributions
AbstractOnly 14 pages are availabe for public view
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Abstract
In this thesis, two new lifetime distributions are proposed. The first distribution is the two-component mixture of the flexible Weibull extension and Burr XII distributions, while the second one is the additive flexible Weibull extension-Burr XII distribution, which is a competing risks model of two different distributions. Several statistical properties of the two proposed distributions are studied. In addition, the characterization of the different shapes for the failure rate of the proposed distributions are discussed in details. The flexibility of the proposed distributions is illustrated by showing their capability of fitting different real data sets compared to some existing distributions using different information criteria. Furthermore, this thesis also focuses on the estimation of the two new distributions under an adaptive Type-II progressive censoring scheme. Point estimation using the maximum likelihood method and asymptotic confidence intervals of the unknown parameters are established. Using the adaptive Metropolis algorithm, Bayesian estimation of the unknown parameters are also carried out under symmetric and asymmetric loss functions. In addition, the Bayesian credible intervals are constructed. A comprehensive simulation study is carried out to assess the performance of the estimates assuming different sample sizes, test termination times, parameter values, and censoring schemes. Moreover, numerical examples using real data sets are analyzed to illustrate the proposed estimation methods