Prediction of Exponentiated Family Distributions Observables under Type-II Hybrid Censored Data

The current study addresses Bayesian prediction intervals for exponentiated family distributions observables under Type-II hybrid censored data. It includes a set of exponentiated distributions such as exponentiated linear failure rate, exponentiated Weibull (EW), exponentiated modified Weibull, exponentiated Rayleigh (ER), exponentiated exponential (EE) distributions...etc. One and two-sample Bayesian predictive survival function under Type-II hybrid censored data are derived. Markov chain Monte Carlo (MCMC) sampling method utilized to generate samples from posterior distributions and Bayesian prediction intervals calculated. Numerical results obtained under two exponentiated distributions, EE(d ) distribution when d is unknown and ER(d ,g ) distribution when parameters d and g are unknown