Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications

The measure of entropy has an undeniable pivotal role in the field of information theory. This article estimates the Rényi and q-entropies of the power function distribution in the presence of s outliers. The maximum likelihood estimators as well as the Bayesian estimators under uniform and gamma pr...

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Autores principales:	Amal Soliman Hassan, Elsayed Ahmed Elsherpieny, Rokaya Elmorsy Mohamed
Formato:	article
Lenguaje:	EN
Publicado:	UUM Press 2021
Materias:	bayesian estimators maximum likelihood estimators outliers power-function distribution rényi entropy Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/0706ef5a734b454ca6ae2c46560b3e7c
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spelling	oai:doaj.org-article:0706ef5a734b454ca6ae2c46560b3e7c2021-11-14T08:23:34ZEstimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications10.32890/jict2022.21.1.11675-414X2180-3862https://doaj.org/article/0706ef5a734b454ca6ae2c46560b3e7c2021-11-01T00:00:00Zhttp://e-journal.uum.edu.my/index.php/jict/article/view/jict2022.21.1.1https://doaj.org/toc/1675-414Xhttps://doaj.org/toc/2180-3862The measure of entropy has an undeniable pivotal role in the field of information theory. This article estimates the Rényi and q-entropies of the power function distribution in the presence of s outliers. The maximum likelihood estimators as well as the Bayesian estimators under uniform and gamma priors are derived. The proposed Bayesian estimators of entropies under symmetric and asymmetric loss functions are obtained. These estimators are computed empirically using Monte Carlo simulation based on Gibbs sampling. Outcomes of the study showed that the precision of the maximum likelihood and Bayesian estimates of both entropies measures improves with sample sizes. The behavior of both entropies estimates increase with number of outliers. Further, Bayesian estimates of the Rényi and q-entropies under squared error loss function are preferable than the other Bayesian estimates under the other loss functions in most of cases. Eventually, real data examples are analyzed to illustrate the theoretical results. Amal Soliman HassanElsayed Ahmed ElsherpienyRokaya Elmorsy MohamedUUM Pressarticlebayesian estimatorsmaximum likelihood estimatorsoutlierspower-function distributionrényi entropyInformation technologyT58.5-58.64ENJournal of ICT, Vol 21, Iss 1, Pp 1-25 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	bayesian estimators maximum likelihood estimators outliers power-function distribution rényi entropy Information technology T58.5-58.64
spellingShingle	bayesian estimators maximum likelihood estimators outliers power-function distribution rényi entropy Information technology T58.5-58.64 Amal Soliman Hassan Elsayed Ahmed Elsherpieny Rokaya Elmorsy Mohamed Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications
description	The measure of entropy has an undeniable pivotal role in the field of information theory. This article estimates the Rényi and q-entropies of the power function distribution in the presence of s outliers. The maximum likelihood estimators as well as the Bayesian estimators under uniform and gamma priors are derived. The proposed Bayesian estimators of entropies under symmetric and asymmetric loss functions are obtained. These estimators are computed empirically using Monte Carlo simulation based on Gibbs sampling. Outcomes of the study showed that the precision of the maximum likelihood and Bayesian estimates of both entropies measures improves with sample sizes. The behavior of both entropies estimates increase with number of outliers. Further, Bayesian estimates of the Rényi and q-entropies under squared error loss function are preferable than the other Bayesian estimates under the other loss functions in most of cases. Eventually, real data examples are analyzed to illustrate the theoretical results.
format	article
author	Amal Soliman Hassan Elsayed Ahmed Elsherpieny Rokaya Elmorsy Mohamed
author_facet	Amal Soliman Hassan Elsayed Ahmed Elsherpieny Rokaya Elmorsy Mohamed
author_sort	Amal Soliman Hassan
title	Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications
title_short	Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications
title_full	Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications
title_fullStr	Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications
title_full_unstemmed	Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications
title_sort	estimation of information measures for power-function distribution in presence of outliers and their applications
publisher	UUM Press
publishDate	2021
url	https://doaj.org/article/0706ef5a734b454ca6ae2c46560b3e7c
work_keys_str_mv	AT amalsolimanhassan estimationofinformationmeasuresforpowerfunctiondistributioninpresenceofoutliersandtheirapplications AT elsayedahmedelsherpieny estimationofinformationmeasuresforpowerfunctiondistributioninpresenceofoutliersandtheirapplications AT rokayaelmorsymohamed estimationofinformationmeasuresforpowerfunctiondistributioninpresenceofoutliersandtheirapplications
_version_	1718429755564359680

Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications

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