Bayesian Estimation and Two-sample Prediction Based on Unified Hybrid Censored Sample

Thesis
Publication Abstract: 

: In this paper, a general inverse exponential form of the underlying distribution and a general conjugate prior are used to discuss the maximum likelihood and Bayesian estimation based on unified hybrid censored sample. A general procedure for deriving two-sample Bayesian prediction is developed using unified hybrid censoring scheme. Special cases of the inverse Weibull model such as the inverse exponential and the inverse Rayleigh distributions are then used as illustrative examples. Finally, numerical examples are presented for illustrating all the inferential procedures developed here.