On Classical and Bayesian Reliability of Systems Using Bivariate Generalized Geometric Distribution

نویسندگان

چکیده

Abstract The study of system safety and reliability has always been vital for the quality manufacturing engineers varying fields which generally continuous probability distributions are proposed. Bivariate multivariate candidates while studying more than one characteristic system. In this article, an attempt is made to address issue when systems generate bivariate correlated count datasets. generalized geometric distribution (BGGD) believed serve as a potential candidate model such types Bayesian approach data analysis accommodating uncertainty associated with parameters interest using uninformative informative priors. A real life dataset analyzed in framework results compared those produced by classical approach. Posterior summaries including posterior means, highest density regions, predicted expected frequencies evaluated. Different information criteria evaluated compare inferential methods under study. entire carried out Markov chain Monte Carlo (MCMC) set-up augmentation implemented through WinBUGS.

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ژورنال

عنوان ژورنال: Journal of Statistical Theory and Applications

سال: 2023

ISSN: ['2214-1766', '1538-7887']

DOI: https://doi.org/10.1007/s44199-023-00058-4