Progressive Censored Burr Type-XII Distribution Under Random Removal Scheme: Some Inferences

Abstract

When some sample values at either or both the extremes might have been assorted, a censoring scheme is much useful. Nevertheless, in some reliability experiments, the number of items fell out the experiment cannot be prexed random in some situations. For such situations, a random removal scheme with censoring scheme may oer a good result. Here, a random removal scheme with the Progressive censoring plan is assumed for statis-
tical inference, when ll out items of the experiments cannot be prexed. The analysis of the present discussion has carried out with the help of a real data set for the Burr Type-XII distribution.

Key words: Random Removal Scheme, Progressive Type-II Censoring Plan, ML Estimation, Bayes Estimation, and Bayes Prediction Bound Length.