Kernel Estimation of Mathai-Haubold Entropy and Residual Mathai-Haubold Entropy Functions under α-Mixing Dependence Condition

Q3 Business, Management and Accounting American Journal of Mathematical and Management Sciences Pub Date : 2021-06-07 DOI:10.1080/01966324.2021.1935366
R. Maya, M. Irshad
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引用次数: 2

Abstract

Abstract Mathai and Haubold introduced a new generalized entropy namely Mathai-Haubold entropy and Dar and Al-Zahrani proposed the Mathai-Haubold entropy for the residual life time and called it as residual Mathai-Haubold entropy. In the present paper, we propose nonparametric estimators for the Mathai-Haubold entropy and the residual Mathai-Haubold entropy where the observations under consideration are exhibiting α-mixing (strong mixing) dependence condition. Asymptotic properties of the estimators are established under suitable regular conditions. A Monte Carlo simulation study is carried out to compare the performance of the estimators using the mean squared error. The methods are illustrated using a real data set.
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α-混合相关条件下Mathai-Haubold熵和残差Mathai-Haubold熵函数的核估计
摘要Mathai和Haubold引入了一种新的广义熵,即Mathai Haubold熵,Dar和Al-Zahrani提出了剩余寿命的Mathai Haobold熵,并称之为剩余Mathai Haub熵。在本文中,我们提出了Mathai-Haubold熵和残差Mathai-Houbold熵的非参数估计,其中所考虑的观测值表现出α-混合(强混合)依赖条件。在适当的正则条件下,建立了估计量的渐近性质。进行了蒙特卡罗模拟研究,以比较使用均方误差的估计器的性能。使用实际数据集对这些方法进行了说明。
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来源期刊
American Journal of Mathematical and Management Sciences
American Journal of Mathematical and Management Sciences Business, Management and Accounting-Business, Management and Accounting (all)
CiteScore
2.70
自引率
0.00%
发文量
5
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