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Can I read Kernel Estimation of Mathai-Haubold Entropy and Residual Mathai-Haubold Entropy Functions under α -Mixing Dependence Condition on EtoBox?
Kernel Estimation of Mathai-Haubold Entropy and Residual Mathai-Haubold Entropy Functions under α -Mixing Dependence Condition by R. Maya; M. R. Irshad is a Mathematics article available to read on EtoBox.
What is Kernel Estimation of Mathai-Haubold Entropy and Residual Mathai-Haubold Entropy Functions under α -Mixing Dependence Condition about?
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 a-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.
Who reads Kernel Estimation of Mathai-Haubold Entropy and Residual Mathai-Haubold Entropy Functions under α -Mixing Dependence Condition?
It is typically read by researchers, students, and practitioners in Mathematics.
- Author
- R. Maya; M. R. Irshad
- Publisher
- Informa UK Limited
- Published
- 2021
- Language
- EN
- Field
- Mathematics (Physical Sciences)