A Novel Zero-Truncated Katz Distribution by the Lagrange Expansion of the Second Kind with Associated Inferences

D. S. Shibu, C. Chesneau, M. Monisha, R. Maya, M. Irshad
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Abstract

In this article, the Lagrange expansion of the second kind is used to generate a novel zero-truncated Katz distribution; we refer to it as the Lagrangian zero-truncated Katz distribution (LZTKD). Notably, the zero-truncated Katz distribution is a special case of this distribution. Along with the closed form expression of all its statistical characteristics, the LZTKD is proven to provide an adequate model for both underdispersed and overdispersed zero-truncated count datasets. Specifically, we show that the associated hazard rate function has increasing, decreasing, bathtub, or upside-down bathtub shapes. Moreover, we demonstrate that the LZTKD belongs to the Lagrangian distribution of the first kind. Then, applications of the LZTKD in statistical scenarios are explored. The unknown parameters are estimated using the well-reputed method of the maximum likelihood. In addition, the generalized likelihood ratio test procedure is applied to test the significance of the additional parameter. In order to evaluate the performance of the maximum likelihood estimates, simulation studies are also conducted. The use of real-life datasets further highlights the relevance and applicability of the proposed model.
用带关联推论的第二类拉格朗日展开的一种新的零截尾Katz分布
本文利用第二类的拉格朗日展开生成了一种新的零截尾Katz分布;我们称之为拉格朗日零截断卡茨分布(LZTKD)。值得注意的是,零截断的Katz分布是该分布的一种特殊情况。随着其所有统计特征的封闭形式表达,LZTKD被证明为欠分散和过分散的零截断计数数据集提供了一个适当的模型。具体来说,我们展示了相关的危险率函数具有增加、减少、浴缸或倒立浴缸的形状。进一步证明了LZTKD属于第一类拉格朗日分布。然后,探讨了LZTKD在统计场景中的应用。未知参数的估计使用著名的最大似然方法。此外,应用广义似然比检验程序检验附加参数的显著性。为了评价最大似然估计的性能,还进行了仿真研究。实际数据集的使用进一步突出了所提出模型的相关性和适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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