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Parameter Estimation of the Mixed Generalized Gamma Distribution Using MaximumLikelihood Estimation and Minimum Distance Estimation

机译:基于最大似然估计和最小距离估计的混合广义Gamma分布参数估计

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The Generalized Gamma is an extremely flexible distribution that is useful forreliability modeling. Among its many special cases are the Weibull and Exponential distributions. A mixture of Generalized Gamma Distributions is even more useful because multiple causes of failure can he simultaneously modeled. This research studied parameter estimation of the special cases of the Mixed Generalized Gamma Distribution and built upon them until the full nine-parameter distribution was being estimated. First, special cases of a single Generalized Gamma Distribution were estimated. Next, mixtures of Exponential distributions with both known and unknown location parameters were estimated. Next, mixtures of Weibull distributions with both known and unknown location parameters were

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