A study on the mixture of exponentiated-weibull distribution part ii (the method of bayesian estimation)

The use of finite mixture distributions,to control for unobserved heterogeneity,has become increasingly popular among those estimating dynamic discrete choice models. one of the barriers to using mixture models is that parameters that could previously be estimated in stages must now be estimated jointly: using mixture distributions destroys any additive reparability of the log likelihood function. in this research,bayesian estimators have been obtained for the parameters of the mixture of exponentiated weibull distribution when sample is available from censoring scheme. the maximum likelihood estimators of the parameters and the asymptotic variance covariance matrix have been obtained by elshahat and mahmoud (2016). bayes and approximate bayes (lindley's form) estimators have been developed under squared error loss function as well as under linex loss function using non -informative type of priors for the parameters will be obtained. a numerical illustration for these new results is given. © 2016,pak.j.stat.oper.res. all rights reserved.