bayesian inference for the power modified lindley distribution based on symmetric and asymmetric balanced loss functions

In this paper, maximum likelihood and bayes estimators of the parameters have been obtained for power modified lindley distribution when sample is available from progressive type-ii censoring scheme. the bayes estimators are obtained under symmetric and asymmetric balanced loss functions, specifically the balanced squared error loss function, the balanced linear exponential loss function. because the integrals of the bayes estimates do not possess closed forms, the metropolis-hastings algorithm is applied to approximate these integrals. one real data sets have been analyzed to demonstrate how the proposed methods can be used in practice.