Bayesian estimation of the parameters of the Weibull log-logistic mixture distributions using time censored data

Abstract EN

This paper is about studying the mixture of the Weibull−log−logistic distributions under Bayesian perspective.

This model can be considered as new class of flexible models for heterogeneous lifetime data.

Parameters of the model are estimated using the Gibbs sampling technique under type I censoring scheme.

The behaviour of the Bayes estimators is studied assuming different priors.

Finally, the model is applied to a real data set.