Some new findings on the survival Rényi entropy and application of COVID-19 data

Motivated by the connotation of survival Rényi entropy and its related dynamic version, we introduce them in terms of their lower bounds and mean residual life function. Moreover, we illustrate the relation between survival Rényi entropy and some of measures of information. Furthermore, the hazard r...

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Autores principales: Mohamed, Mohamed S., Almohaimeed, Amani, Abd El-Raouf, Mahmoud M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8608416/
https://www.ncbi.nlm.nih.gov/pubmed/34840939
http://dx.doi.org/10.1016/j.rinp.2021.104966
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author Mohamed, Mohamed S.
Almohaimeed, Amani
Abd El-Raouf, Mahmoud M.
author_facet Mohamed, Mohamed S.
Almohaimeed, Amani
Abd El-Raouf, Mahmoud M.
author_sort Mohamed, Mohamed S.
collection PubMed
description Motivated by the connotation of survival Rényi entropy and its related dynamic version, we introduce them in terms of their lower bounds and mean residual life function. Moreover, we illustrate the relation between survival Rényi entropy and some of measures of information. Furthermore, the hazard rate order implies ordering of dynamic survival Rényi entropy. Our models are considered a more comprehensive version of generalized order statistics and give some properties and characterization results. Finally, a non-parametric estimation of survival Rényi entropy is included based on real COVID-19 data and simulated data.
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spelling pubmed-86084162021-11-23 Some new findings on the survival Rényi entropy and application of COVID-19 data Mohamed, Mohamed S. Almohaimeed, Amani Abd El-Raouf, Mahmoud M. Results Phys Article Motivated by the connotation of survival Rényi entropy and its related dynamic version, we introduce them in terms of their lower bounds and mean residual life function. Moreover, we illustrate the relation between survival Rényi entropy and some of measures of information. Furthermore, the hazard rate order implies ordering of dynamic survival Rényi entropy. Our models are considered a more comprehensive version of generalized order statistics and give some properties and characterization results. Finally, a non-parametric estimation of survival Rényi entropy is included based on real COVID-19 data and simulated data. The Author(s). Published by Elsevier B.V. 2021-12 2021-11-23 /pmc/articles/PMC8608416/ /pubmed/34840939 http://dx.doi.org/10.1016/j.rinp.2021.104966 Text en © 2021 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Mohamed, Mohamed S.
Almohaimeed, Amani
Abd El-Raouf, Mahmoud M.
Some new findings on the survival Rényi entropy and application of COVID-19 data
title Some new findings on the survival Rényi entropy and application of COVID-19 data
title_full Some new findings on the survival Rényi entropy and application of COVID-19 data
title_fullStr Some new findings on the survival Rényi entropy and application of COVID-19 data
title_full_unstemmed Some new findings on the survival Rényi entropy and application of COVID-19 data
title_short Some new findings on the survival Rényi entropy and application of COVID-19 data
title_sort some new findings on the survival rényi entropy and application of covid-19 data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8608416/
https://www.ncbi.nlm.nih.gov/pubmed/34840939
http://dx.doi.org/10.1016/j.rinp.2021.104966
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