학술논문

A Bayes Analysis of a Dependent Competing Risk Model Based on Marshall–Olkin Bivariate Weibull Distribution.
Document Type
Article
Source
International Journal of Reliability, Quality & Safety Engineering. Jun2023, Vol. 30 Issue 3, p1-29. 29p.
Subject
*Bayesian analysis
Weibull distribution
Competing risks
Gibbs sampling
Accelerated life testing
Models & modelmaking
Bivariate analysis
Language
ISSN
0218-5393
Abstract
This paper considers a competing risk model defined on the basis of minimum of two dependent failures where the two failures are assumed to jointly follow Marshall–Olkin bivariate Weibull distribution. This paper explores some important features of corresponding likelihood functions and performs a full Bayesian analysis of the model for data resulting from normal as well as accelerated life tests. The accelerated model is described by regressing the scale parameters of the model through inverse power-law relationship. Posterior-based inferences are drawn using the Gibbs sampler algorithm after specifying proper but vague priors for the model parameters. The numerical illustration is provided using real datasets. The performance of the model is assured by Bayesian tools of model compatibility and then the entertained model is compared with the competing risk model based on Marshall–Olkin bivariate exponential assumption. [ABSTRACT FROM AUTHOR]