الفهرس 
Discriminating among competitive distributions under censored samples
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Abstract
In this thesis the problem of discriminating between weibull and log logistic distribution, gamma and log logistic distribution under progressive censoring type II is considered. The maximized likelihood ratio test is used to discriminate between them. Also the problem of discriminating between gamma and log logistic under complete sample is considered. The maximized likelihood ratio test and kullback-leibler divergence is used to discriminate between them. Asymptotic distribution of the logarithm of the ratio of the maximized likelihood is obtained. These asymptotic results are used to estimate probability of correct selection, and to obtain the minimum sample size needed to discriminate between the two distribution functions. Two data sets are analyzed for illustrative purpose