Estimation for the Exponentiated Half Logistic Distribution Based on type I Hybrid Censored Samples

In this paper, we derive statistical inference on the shape parameter for the exponentiated half logistic distribution when samples are type I hybrid censored samples. The shape parameter is estimated by the Bayesian method (under square error loss function and linex loss function). We consider conjugate prior and corresponding posterior distribution is obtained. We also obtain the maximum likelihood estimator (MLE) of the shape parameter under the type I hybrid censored samples. We compare the estimators in the sense of the root mean square error (RMSE). The simulation procedure is repeated 10,000 times for the sample size n = 20, 30, 40 and various type I hybrid censored samples. The Bayes estimators under the linex loss function is better than their corresponding MLEs and Bayes estimators under the square error loss function. Further an illustrative example with the real data is presented.