Bayesian prediction interval for a constant-stress partially accelerated life test model under censored data

Autor:	Showkat Ahmad Lone, Hanieh Panahi, Ismail Shah
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	bayesian prediction gompertz distribution unified hybrid censoring monte carlo simulation partially accelerated life test Science (General) Q1-390
Zdroj:	Journal of Taibah University for Science, Vol 15, Iss 1, Pp 1178-1187 (2021)
Druh dokumentu:	article
ISSN:	1658-3655 16583655
DOI:	10.1080/16583655.2021.2023847
Popis:	The present communication develops the tools for Bayesian prediction of the Gompertz distribution based on CSPALT. The Metropolis-Hastings algorithm is applied to evaluate the BPIs for a censored sample based on unified hybrid censoring scheme. In order to investigate the impact of methodologies adopted, two numerical examples are performed. The simulated results show that reducing the censoring percentages causes smaller BPIs. The flexibility of the UHCS in evaluating the BPIs can be helped to overcome many difficulties in engineering problems.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/3f7b57c381994536b43f23a13b2cd57c Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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