Estimation of the coefficient of variation for lindley distribution based on progressive first failure censored data

In applied statistics, the coefficient of variation (CV) of a distribution is considered as one of the useful descriptive measures for describing variability. However, inferences concerning the coefficient of variation of non-normal distributions are rarely reported. In this paper, estimation of CV using progressive first failure censored data for the Lindley distribution (LD) is developed. A point estimation as well as interval estimation of CV aure obtained using Bayesian and non-Bayesian approaches. In Bayesian approach, we obtian the Bayes estimation with both the symmetric and asymmetric loss fnctions. Results from simulation studies assessing the performance of the maximum likelihood estimation (MLE) and Bayes estimates are included.