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A new bivariate distribution with weighted exponential marginals and its multivariate generalization

机译:具有加权指数边际的新二元分布及其多元泛化

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摘要

Gupta and Kundu (Statistics 43:621–643, 2009) recently introduced a new class of weighted exponential distribution. It is observed that the proposed weighted exponential distribution is very flexible and can be used quite effectively to analyze skewed data. In this paper we propose a new bivariate distribution with the weighted exponential marginals. Different properties of this new bivariate distribution have been investigated. This new family has three unknown parameters, and it is observed that the maximum likelihood estimators of the unknown parameters can be obtained by solving a one-dimensional optimization procedure. We obtain the asymptotic distribution of the maximum likelihood estimators. Small simulation experiments have been performed to see the behavior of the maximum likelihood estimators, and one data analysis has been presented for illustrative purposes. Finally we discuss the multivariate generalization of the proposed model.
机译:Gupta和Kundu(Statistics 43:621–643,2009)最近引入了一类新的加权指数分布。可以看出,建议的加权指数分布非常灵活,可以非常有效地用于分析偏斜数据。在本文中,我们提出了一个新的具有加权指数边际的双变量分布。已经研究了这种新的双变量分布的不同性质。该新族具有三个未知参数,并且观察到,可以通过求解一维优化过程来获得未知参数的最大似然估计。我们获得最大似然估计量的渐近分布。已经进行了小型仿真实验,以查看最大似然估计器的行为,并且出于说明目的提供了一种数据分析。最后,我们讨论了所提出模型的多元概括。

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