Analysis for Xgamma Parameters of Life under Type-II Adaptive Progressively Hybrid Censoring with Applications in Engineering and Chemistry

Censoring mechanisms are widely used in various life tests, such as medicine, engineering, biology, etc., as they save (overall) test time and cost. In this context, we consider the problem of estimating the unknown xgamma parameter and some survival characteristics, such as reliability and failure...

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Autores principales:	Ahmed Elshahhat, Berihan R. Elemary
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	adaptive progressively hybrid censoring Bayes estimator maximum likelihood estimator Metropolis–Hasting algorithm reliability characteristics xgamma distribution Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/2d47473fcadb4f7bb4479d71b451be28
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spelling	oai:doaj.org-article:2d47473fcadb4f7bb4479d71b451be282021-11-25T19:06:50ZAnalysis for Xgamma Parameters of Life under Type-II Adaptive Progressively Hybrid Censoring with Applications in Engineering and Chemistry10.3390/sym131121122073-8994https://doaj.org/article/2d47473fcadb4f7bb4479d71b451be282021-11-01T00:00:00Zhttps://www.mdpi.com/2073-8994/13/11/2112https://doaj.org/toc/2073-8994Censoring mechanisms are widely used in various life tests, such as medicine, engineering, biology, etc., as they save (overall) test time and cost. In this context, we consider the problem of estimating the unknown xgamma parameter and some survival characteristics, such as reliability and failure rate functions in the presence of adaptive type-II progressive hybrid censored data. For this purpose, the maximum likelihood and Bayesian inferential approaches are used. Using the observed Fisher information under s-normal approximation, different asymptotic confidence intervals for any function of the unknown parameter were constructed. Using the gamma flexible prior, Bayes estimators against the squared-error loss were developed. Two procedures of Bayesian approximations—Lindley’s approximation and Metropolis–Hastings algorithm—were used to carry out the Bayes estimates and to construct the associated credible intervals. An extensive simulation study was implemented to compare the performance of the different methods. To validate the proposed methodologies of inference—two practical studies using datasets that form engineering and chemical fields are discussed.Ahmed ElshahhatBerihan R. ElemaryMDPI AGarticleadaptive progressively hybrid censoringBayes estimatormaximum likelihood estimatorMetropolis–Hasting algorithmreliability characteristicsxgamma distributionMathematicsQA1-939ENSymmetry, Vol 13, Iss 2112, p 2112 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	adaptive progressively hybrid censoring Bayes estimator maximum likelihood estimator Metropolis–Hasting algorithm reliability characteristics xgamma distribution Mathematics QA1-939
spellingShingle	adaptive progressively hybrid censoring Bayes estimator maximum likelihood estimator Metropolis–Hasting algorithm reliability characteristics xgamma distribution Mathematics QA1-939 Ahmed Elshahhat Berihan R. Elemary Analysis for Xgamma Parameters of Life under Type-II Adaptive Progressively Hybrid Censoring with Applications in Engineering and Chemistry
description	Censoring mechanisms are widely used in various life tests, such as medicine, engineering, biology, etc., as they save (overall) test time and cost. In this context, we consider the problem of estimating the unknown xgamma parameter and some survival characteristics, such as reliability and failure rate functions in the presence of adaptive type-II progressive hybrid censored data. For this purpose, the maximum likelihood and Bayesian inferential approaches are used. Using the observed Fisher information under s-normal approximation, different asymptotic confidence intervals for any function of the unknown parameter were constructed. Using the gamma flexible prior, Bayes estimators against the squared-error loss were developed. Two procedures of Bayesian approximations—Lindley’s approximation and Metropolis–Hastings algorithm—were used to carry out the Bayes estimates and to construct the associated credible intervals. An extensive simulation study was implemented to compare the performance of the different methods. To validate the proposed methodologies of inference—two practical studies using datasets that form engineering and chemical fields are discussed.
format	article
author	Ahmed Elshahhat Berihan R. Elemary
author_facet	Ahmed Elshahhat Berihan R. Elemary
author_sort	Ahmed Elshahhat
title	Analysis for Xgamma Parameters of Life under Type-II Adaptive Progressively Hybrid Censoring with Applications in Engineering and Chemistry
title_short	Analysis for Xgamma Parameters of Life under Type-II Adaptive Progressively Hybrid Censoring with Applications in Engineering and Chemistry
title_full	Analysis for Xgamma Parameters of Life under Type-II Adaptive Progressively Hybrid Censoring with Applications in Engineering and Chemistry
title_fullStr	Analysis for Xgamma Parameters of Life under Type-II Adaptive Progressively Hybrid Censoring with Applications in Engineering and Chemistry
title_full_unstemmed	Analysis for Xgamma Parameters of Life under Type-II Adaptive Progressively Hybrid Censoring with Applications in Engineering and Chemistry
title_sort	analysis for xgamma parameters of life under type-ii adaptive progressively hybrid censoring with applications in engineering and chemistry
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/2d47473fcadb4f7bb4479d71b451be28
work_keys_str_mv	AT ahmedelshahhat analysisforxgammaparametersoflifeundertypeiiadaptiveprogressivelyhybridcensoringwithapplicationsinengineeringandchemistry AT berihanrelemary analysisforxgammaparametersoflifeundertypeiiadaptiveprogressivelyhybridcensoringwithapplicationsinengineeringandchemistry
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Analysis for Xgamma Parameters of Life under Type-II Adaptive Progressively Hybrid Censoring with Applications in Engineering and Chemistry

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