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Abstract
In this thesis, we introduce a new five-parameter continuous model, called the beta generalized linear failure rate (BGLFR) distribution, to extend the three parameters generalized linear failure rate (GLFR) distribution. The new distribution is quite flexible and can be used effectively in modeling survival data and reliability problems. It can have a constant, decreasing, increasing, upside down bathtub and bathtub shaped failure rate function depending on its parameters. It includes some well-known lifetime distributions as special sub-models. Some structural properties of the new distribution are studied. We give a mathematical treatment of the new distribution including expansions for the density function, moments, moment generating and quantile functions, mean deviations, entropy, reliability measures, and order statistics. The model parameters are estimated by maximum likelihood and moment methods. The observed information matrix is derived. Two applications of the new model to real data show that it can give consistently a better fit than other important lifetime models