estimation parameters of lindley distribution under type ii progressive censoring with the presence of outlier data

Lindley distribution is one of the most important statistical distributions that is widely used in various fields including biology‎, ‎engineering‎, ‎and medicine‎. ‎this distribution has worked well in modeling mortality studies‎, ‎and this distribution can be used for statistical modeling of plant roots density‎. ‎recently‎, ‎a number of researchers have shown that statistical distributions can be used to model or investigate the number of plant roots‎. ‎one of the most important of these is the lindley distribution‎, ‎which can be used to investigate modeling data in the presence of outliers that have a lindley or uniform distribution‎. ‎in this article‎, ‎we present the lindley distribution under type ii progressive censoring with the presence of outlier data‎, ‎and its parameters are estimated using maximum likelihood and bayesian methods‎. ‎in the following‎, ‎by applying gibbs sampling and performing simulation‎, ‎the estimators are compared with each other using the mean squared error.