Estimation of Parameters of Inverse Lomax Distribution under Type-II Censoring Scheme

In this paper, Bayesian and E-Bayesian estimation of unknown parameters of Inverse Lomax probability distribution based on Type-II censored samples has been obtained under De Groot Loss Function (DLF), Al-Bayyati Loss function (ABLF), Entropy Loss Function (ELF), Linex Loss Function (LLF) and Minimum Expected Loss Function (MELF). To derive these estimators, we have considered a conjugate gamma prior and uniform hyperprior distributions. The Monte Carlo simulation method has been used to generate a Type-II censored data from Inverse Lomax probability distribution. The performance of the estimators has been tested and compared by computing mean square error (MSE). Further, the relationship between the E-Bayesian estimators has been established in the form of theorems