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A New Gumbel Generated Family of Distributions: Properties, Bivariate Distribution and Application

机译:新的Gumbel生成的分布系列:属性,双变量分配和应用

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In this paper, we propose a new class of Gumbel generated distributions called Gumbel-Marshall-Olkin family of distributions. The new family of distributions is represented as linear mixture of exponentiated-G distribution. Some of the sub-models are presented. We derived some characterizations such as the quantile, moments, moment generating function, entropy and order statistics of the proposed family of distributions. The estimation of the unknown parameters of the new class of distribution is through the maximum likelihood. The consistency of the MLEs of the sub-model is assessed by means of simulation. Furthermore, we derive the bivariate density function of the new class of distributions. Two real life data sets are used to illustrate the potential usefulness of the sub-models of the proposed class of distributions. The results of the applications clearly indicate that the sub-models of the proposed class of distribution provided better fit among the other competing models.
机译:在本文中,我们提出了一类名为Gumbel-Marshall-Olkin系列分布的新一类Gumbel产生的分布。新的分布系列表示为指数-G分布的线性混合物。一些子模型呈现。我们派生了一些特征,例如拟议的分布系列的分位数,时刻,时刻生成函数,熵和订单统计。估计新的分布类的未知参数是通过最大可能性。通过模拟评估子模型的MLE的一致性。此外,我们推出了新类分布的双变量密度函数。两个真实生活数据集用于说明所提出的分布类的子模型的潜在有用性。应用程序的结果清楚地表明,拟议的分配类的子模型在其他竞争模式中提供了更好的适合。

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