الفهرس 
Introduction and Review of LiteratureOnly 14 pages are availabe for public view
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Abstract
In reliability and life-testing experiments, the researcher is often interested in the effects of extreme or varying stress factors such a temperature, voltage, load or any other factor that directly affects the lifetimes of experimental units. One of the important technical structures in reliability analysis is called the accelerated life-testing (ALT) experiment. Such an experiment enables the experimenter to obtain enough lifetime data for the product under accelerated stress conditions, which reason the products to fail more quickly than under the normal operating conditions.
The step stress testing is a special class of ALT. The step stress testing allows the experimenter to increase the stress levels at fixed times during the experiment in order to obtain information on the parameters of the life distributions more quickly than under normal operating conditions.
In this thesis, we discuss a simple step-stress model under Burr XII distribution when available data are (1) Type-II censored, (2) Type-I censored, (3) Type-II hybrid censored, (4) Type-I hybrid censored. We use three methods for estimation (1) Maximum likelihood method, (2) EM-algorithm method, (3) Bayesian method. We obtain the estimators of the unknown parameters with respect to a cumulative exposure model. In addition, asymptotic variance and covariance matrix of the estimators are given. Furthermore, confidence intervals of the estimators are presented. The performance of the finding in the thesis is showed by demonstrating some numerical illustration through Monte Carlo.