The E-Bayesian Estimation for Lomax Distribution Based on Generalized Type-I Hybrid Censoring Scheme

This article studies the E-Bayesian estimation of unknown parameter Lomax distribution based on generalized Type-I hybrid censoring. Under square error loss and LINEX functions, we get compare its effectiveness with Bayesian estimation. To measure estimation, expectation mean (E-MSE) is introduced. With Markov chain Monte Carlo technology, estimations are computed. Metropolis–Hastings algorithm applied within process. Similarly, credible interval for calculated. Then, can MSE E-MSE to evaluate whose result more effective. For purpose illustration in real datasets, cases censored samples presented. In order judge whether sample data be directly fitted by distribution, adopt Kolmogorov–Smirnov tests evaluation. Finally, conclusion after comparing results