Analysis of block adaptive type-II progressive hybrid censoring with Weibull distribution

doi:10.3390/math12244026

機構典藏 > College of Business and Management > Graduate Institute & Department of Statistics > Journal Article > Item 987654321/126927

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/126927

Title:	Analysis of block adaptive type-II progressive hybrid censoring with Weibull distribution
Authors:	Singh, Kundan;Tripathi, Yogesh Mani;Wang, Liang;Wu, Shuo-Jye
Keywords:	censoring;Weibull distribution;Metropolis–Hastings algorithm;difference in testing facilities
Date:	2024-12-16
Issue Date:	2025-03-20 09:31:14 (UTC+8)
Abstract:	The estimation of unknown model parameters and reliability characteristics is considered under a block adaptive progressive hybrid censoring scheme, where data are observed from a Weibull model. This censoring scheme enhances experimental efficiency by conducting experiments across different testing facilities. Point and interval estimates for parameters and reliability assessments are derived using both classical and Bayesian approaches. The existence and uniqueness of maximum likelihood estimates are established. Consequently, reliability performance and differences across different testing facilities are analyzed. In addition, a Metropolis–Hastings sampling algorithm is developed to approximate complex posterior computations. Approximate confidence intervals and highest posterior density credible intervals are obtained for the parametric functions. The performance of all estimators is evaluated through an extensive simulation study, and observations are discussed. A cancer dataset is analyzed to illustrate the findings under the block adaptive censoring scheme.
Relation:	Mathematics, Vol. 12, No. 24, 4026.
DOI:	10.3390/math12244026
Appears in Collections:	[Graduate Institute & Department of Statistics] Journal Article

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