Ordered Variables and Their Concomitants under Extropy via COVID-19 Data Application
Said, Mohamed; Alanazi Talal Abdulrahman; Zahra Almaspoor; M. Yusuf;
Abstract
Extropy, as a complementary dual of entropy, has been discussed in many works of literature, where it is declared for other
measures as an extension of extropy. In this article, we obtain the extropy of generalized order statistics via its dual and give some
examples from well-known distributions. Furthermore, we study the residual and past extropy for such models. On the other
hand, based on Farlie–Gumbel–Morgenstern distribution, we consider the residual extropy of concomitants of m-generalized
order statistics and present this measure with some additional features. In addition, we provide the upper bound and stochastic
orders of it. Finally, nonparametric estimation of the residual extropy of concomitants of m-generalized order statistics is included
using simulated and real data connected with COVID-19 virus.
measures as an extension of extropy. In this article, we obtain the extropy of generalized order statistics via its dual and give some
examples from well-known distributions. Furthermore, we study the residual and past extropy for such models. On the other
hand, based on Farlie–Gumbel–Morgenstern distribution, we consider the residual extropy of concomitants of m-generalized
order statistics and present this measure with some additional features. In addition, we provide the upper bound and stochastic
orders of it. Finally, nonparametric estimation of the residual extropy of concomitants of m-generalized order statistics is included
using simulated and real data connected with COVID-19 virus.
Other data
Title | Ordered Variables and Their Concomitants under Extropy via COVID-19 Data Application | Authors | Said, Mohamed ; Alanazi Talal Abdulrahman; Zahra Almaspoor; M. Yusuf | Issue Date | 6-Jul-2021 | Publisher | Hindawi | Journal | Complexity | Volume | 2021 | DOI | https://doi.org/10.1155/2021/6491817 |
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