Type I Half Logistic Burr X-G Family: Properties, Bayesian, and Non-Bayesian Estimation under Censored Samples and Applications to COVID-19 Data

In this paper, we present a new family of continuous distributions known as the type I half logistic Burr X-G. The proposed family’s essential mathematical properties, such as quantile function (QuFu), moments (Mo), incomplete moments (InMo), mean deviation (MeD), Lorenz (Lo) and Bonferroni (Bo) cur...

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Autores principales:	Ali Algarni, Abdullah M. Almarashi, I. Elbatal, Amal S. Hassan, Ehab M. Almetwally, Abdulkader M. Daghistani, Mohammed Elgarhy
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/471ad1f1a77049a7b205cc069f4a603c
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spelling	oai:doaj.org-article:471ad1f1a77049a7b205cc069f4a603c2021-11-08T02:36:31ZType I Half Logistic Burr X-G Family: Properties, Bayesian, and Non-Bayesian Estimation under Censored Samples and Applications to COVID-19 Data1563-514710.1155/2021/5461130https://doaj.org/article/471ad1f1a77049a7b205cc069f4a603c2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/5461130https://doaj.org/toc/1563-5147In this paper, we present a new family of continuous distributions known as the type I half logistic Burr X-G. The proposed family’s essential mathematical properties, such as quantile function (QuFu), moments (Mo), incomplete moments (InMo), mean deviation (MeD), Lorenz (Lo) and Bonferroni (Bo) curves, and entropy (En), are provided. Special models of the family are presented, including type I half logistic Burr X-Lomax, type I half logistic Burr X-Rayleigh, and type I half logistic Burr X-exponential. The maximum likelihood (MLL) and Bayesian techniques are utilized to produce parameter estimators for the recommended family using type II censored data. Monte Carlo simulation is used to evaluate the accuracy of estimates for one of the family’s special models. The COVID-19 real datasets from Italy, Canada, and Belgium are analysed to demonstrate the significance and flexibility of some new distributions from the family.Ali AlgarniAbdullah M. AlmarashiI. ElbatalAmal S. HassanEhab M. AlmetwallyAbdulkader M. DaghistaniMohammed ElgarhyHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Ali Algarni Abdullah M. Almarashi I. Elbatal Amal S. Hassan Ehab M. Almetwally Abdulkader M. Daghistani Mohammed Elgarhy Type I Half Logistic Burr X-G Family: Properties, Bayesian, and Non-Bayesian Estimation under Censored Samples and Applications to COVID-19 Data
description	In this paper, we present a new family of continuous distributions known as the type I half logistic Burr X-G. The proposed family’s essential mathematical properties, such as quantile function (QuFu), moments (Mo), incomplete moments (InMo), mean deviation (MeD), Lorenz (Lo) and Bonferroni (Bo) curves, and entropy (En), are provided. Special models of the family are presented, including type I half logistic Burr X-Lomax, type I half logistic Burr X-Rayleigh, and type I half logistic Burr X-exponential. The maximum likelihood (MLL) and Bayesian techniques are utilized to produce parameter estimators for the recommended family using type II censored data. Monte Carlo simulation is used to evaluate the accuracy of estimates for one of the family’s special models. The COVID-19 real datasets from Italy, Canada, and Belgium are analysed to demonstrate the significance and flexibility of some new distributions from the family.
format	article
author	Ali Algarni Abdullah M. Almarashi I. Elbatal Amal S. Hassan Ehab M. Almetwally Abdulkader M. Daghistani Mohammed Elgarhy
author_facet	Ali Algarni Abdullah M. Almarashi I. Elbatal Amal S. Hassan Ehab M. Almetwally Abdulkader M. Daghistani Mohammed Elgarhy
author_sort	Ali Algarni
title	Type I Half Logistic Burr X-G Family: Properties, Bayesian, and Non-Bayesian Estimation under Censored Samples and Applications to COVID-19 Data
title_short	Type I Half Logistic Burr X-G Family: Properties, Bayesian, and Non-Bayesian Estimation under Censored Samples and Applications to COVID-19 Data
title_full	Type I Half Logistic Burr X-G Family: Properties, Bayesian, and Non-Bayesian Estimation under Censored Samples and Applications to COVID-19 Data
title_fullStr	Type I Half Logistic Burr X-G Family: Properties, Bayesian, and Non-Bayesian Estimation under Censored Samples and Applications to COVID-19 Data
title_full_unstemmed	Type I Half Logistic Burr X-G Family: Properties, Bayesian, and Non-Bayesian Estimation under Censored Samples and Applications to COVID-19 Data
title_sort	type i half logistic burr x-g family: properties, bayesian, and non-bayesian estimation under censored samples and applications to covid-19 data
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/471ad1f1a77049a7b205cc069f4a603c
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Type I Half Logistic Burr X-G Family: Properties, Bayesian, and Non-Bayesian Estimation under Censored Samples and Applications to COVID-19 Data

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