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On the Extended Chen Distribution: Development, Properties, Characterizations and Applications

机译:在延长陈分布:开发,属性,特征和应用程序

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In this paper, a flexible model called extended Chen (EC) distribution is derived from the generalized Burr-Hatke differential equation and nexus between the exponential and gamma variables. The EC distribution is also derived from compounding mixture of the generalized Chen and gamma distributions. The EC distribution is very flexible and its hazard rate function accommodates various shapes such as increasing, decreasing, decreasing-increasing, increasing-decreasing-increasing, bathtub and modified bathtub. The density function of the EC model is arc, J, reverse-J, left-skewed, right-skewed and symmetrical shaped. Some structural and mathematical properties such as descriptive measures on the basis of quantiles, stochastic orderings, moments, order statistics and reliability measures are theoretically established. The EC distribution is characterized via various techniques. The maximum likelihood estimates for unknown parameters of the EC distribution are obtained. A simulation study is executed to assess the behavior of the maximum likelihood estimators. The EC distribution is applied to two real data sets to elucidate its potentiality and utility. The competence of the EC distribution is tested through arious goodness of fit criteria.
机译:在本文中,从指数和伽马变量之间的广义Burr-Hatke微分方程和Nexus导出了一种称为扩展陈(EC)分布的柔性模型。 EC分布也来自于广义陈和γ分布的复合混合物。 EC分布非常灵活,其危险率函数适应各种形状,例如增加,减小,增加,增加,增加的增加,浴缸和改性浴缸。 EC模型的密度函数是弧形,J,Reverse-J,左偏斜,右偏斜和对称形状。理论上建立了一些结构和数学属性,如在量级,随机排序,时刻,阶段,订单统计和可靠性措施的基础上的描述性措施。 EC分配的特征在于各种技术。获得了EC分布未知参数的最大似然估计。执行模拟研究以评估最大似然估计的行为。 EC分布应用于两个真实数据集以阐明其潜力和实用程序。通过良好的拟合标准测试EC分配的能力。

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