Statistical Inference and Optimum Life-Testing Plans with Joint Progressively Type-II Censoring Scheme

機構典藏 > College of Sciences > Department of Applied Mathematics and Data Science > Journal Article > Item 987654321/122884

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/122884

Title:	Statistical Inference and Optimum Life-Testing Plans with Joint Progressively Type-II Censoring Scheme
Authors:	Lin, Chien-Tai;Chen, Yen-Chou;Yeh, Tzu-Chi;Ng, Hon Keung Tony
Keywords:	Maximum likelihood estimation;monte carlo simulation;optimal criteria;variable neighborhood search algorithm
Date:	2022-11-11
Issue Date:	2023-04-28 16:22:58 (UTC+8)
Publisher:	Taylor & Francis
Abstract:	This article discusses the estimation of model parameters and the determination of optimal life-testing plans for Weibull-distributed lifetimes under a joint progressive Type-II censoring scheme. We obtain the maximum likelihood estimates numerically and propose a modified variable-neighborhood-search-based approach for determining the optimum joint progressive Type-II censoring scheme. Different optimal criteria, including a cost minimization criterion, the A-optimality criterion, and the D-optimality criterion, are considered. A sensitivity analysis is used to study the effect of misspecification of parameter values on the optimal schemes.
Relation:	Quality Technology & Quantitative Management
DOI:	10.1080/16843703.2022.2071535
Appears in Collections:	[Department of Applied Mathematics and Data Science] Journal Article

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	99	View/Open