用广义指数分布的均值的最大似然值随机增加分组数据

M. Hanif, U. Shahzad, Irum Shahzadi, N. Koyuncu
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引用次数: 2

摘要

广义双参数指数分布具有较好的应用价值。在文献中,广义指数分布均值是通过基于各种数据结构的极大似然估计得到的。然而,在文献中没有发现广义指数分布估计量的保序性质。本文将讨论该属性。用广义指数分布的耦合方法检验分组数据的随机增量。通过极大似然估计对参数进行估计。随着检测时间的随机排序,距离逐渐减小。在连续距离中,单调性的假设被取消。利用马尔可夫性质来实现单调性的假设。学科分类:(2010)60G20。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastically increasing grouped data using the MLE of mean of the generalized exponential distribution
The generalized exponential distribution with two parameters has the verity of applications. In literature, the generalized exponential distribution mean are obtained through maximum likelihood estimators based on various data structures. However, the order preserving property of generalized exponential distribution estimators are not found in the literature. This property discusses in this article. Coupling method is used to check the stochastic increment of grouped data using the generalized exponential distribution. The parameters are estimated through maximum likelihood estimation. The distances are decreasing lies between the inspection times are stochastically ordered. The assumptions of monotonicity are dropped in successive distances. The Markove property is used to attain the assumptions of monotonicity. Subject Classification: (2010) 60G20.
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