Statistical inference for Kumaraswamy-exponential distribution based on progressive Type-II censored data with binomial removals

In this paper, estimation of parameters of Kumaraswamy-exponential distribution with shape parameters α and β is considered based on a progressively type-II censored sample with binomial removals. Together with the unknown parameters, the removal probability p is also estimated. Bayes estimators are obtained using different loss functions such as squared error, LINEX loss function and entropy loss function. All Bayesian estimates are compared with the corresponding maximum likelihood estimates numerically in terms of their bias and mean square error values and found that Bayes estimators perform better than MLEs for β and p and MLEs perform better than Bayes estimators for α. A real data set is also used for illustration.