Estimation and Bayesian Prediction of the Generalized Pareto Distribution in the Context of a Progressive Type-II Censoring Scheme

The generalized Pareto distribution plays a significant role in reliability research. This study concentrates on the statistical inference of the generalized Pareto distribution utilizing progressively Type-II censored data. Estimations are performed using maximum likelihood estimation through the e...

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Main Authors: Tianrui Ye, Wenhao Gui
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/14/18/8433
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author Tianrui Ye
Wenhao Gui
author_facet Tianrui Ye
Wenhao Gui
author_sort Tianrui Ye
collection DOAJ
description The generalized Pareto distribution plays a significant role in reliability research. This study concentrates on the statistical inference of the generalized Pareto distribution utilizing progressively Type-II censored data. Estimations are performed using maximum likelihood estimation through the expectation–maximization approach. Confidence intervals are derived using the asymptotic confidence intervals. Bayesian estimations are conducted using the Tierney and Kadane method alongside the Metropolis–Hastings algorithm, and the highest posterior density credible interval estimation is accomplished. Furthermore, Bayesian predictive intervals and future sample estimations are explored. To illustrate these inference techniques, a simulation and practical example are presented for analysis.
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spelling doaj-art-5be51d741e514150af3b4f2bb3b61a302025-08-20T01:55:58ZengMDPI AGApplied Sciences2076-34172024-09-011418843310.3390/app14188433Estimation and Bayesian Prediction of the Generalized Pareto Distribution in the Context of a Progressive Type-II Censoring SchemeTianrui Ye0Wenhao Gui1Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC 27599, USASchool of Mathematics and Statistics, Beijing Jiaotong University, Beijing 100044, ChinaThe generalized Pareto distribution plays a significant role in reliability research. This study concentrates on the statistical inference of the generalized Pareto distribution utilizing progressively Type-II censored data. Estimations are performed using maximum likelihood estimation through the expectation–maximization approach. Confidence intervals are derived using the asymptotic confidence intervals. Bayesian estimations are conducted using the Tierney and Kadane method alongside the Metropolis–Hastings algorithm, and the highest posterior density credible interval estimation is accomplished. Furthermore, Bayesian predictive intervals and future sample estimations are explored. To illustrate these inference techniques, a simulation and practical example are presented for analysis.https://www.mdpi.com/2076-3417/14/18/8433generalized Pareto distributionexpectation–maximization algorithmprogressive Type-II censoringMetropolis–Hasting approachBayesian estimationBayesian prediction
spellingShingle Tianrui Ye
Wenhao Gui
Estimation and Bayesian Prediction of the Generalized Pareto Distribution in the Context of a Progressive Type-II Censoring Scheme
Applied Sciences
generalized Pareto distribution
expectation–maximization algorithm
progressive Type-II censoring
Metropolis–Hasting approach
Bayesian estimation
Bayesian prediction
title Estimation and Bayesian Prediction of the Generalized Pareto Distribution in the Context of a Progressive Type-II Censoring Scheme
title_full Estimation and Bayesian Prediction of the Generalized Pareto Distribution in the Context of a Progressive Type-II Censoring Scheme
title_fullStr Estimation and Bayesian Prediction of the Generalized Pareto Distribution in the Context of a Progressive Type-II Censoring Scheme
title_full_unstemmed Estimation and Bayesian Prediction of the Generalized Pareto Distribution in the Context of a Progressive Type-II Censoring Scheme
title_short Estimation and Bayesian Prediction of the Generalized Pareto Distribution in the Context of a Progressive Type-II Censoring Scheme
title_sort estimation and bayesian prediction of the generalized pareto distribution in the context of a progressive type ii censoring scheme
topic generalized Pareto distribution
expectation–maximization algorithm
progressive Type-II censoring
Metropolis–Hasting approach
Bayesian estimation
Bayesian prediction
url https://www.mdpi.com/2076-3417/14/18/8433
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