Estimation for coefficient of variation of an extension of the exponential distribution under type-II censoring scheme

Abstract

The coefficient of variation [CV] has several applications in applied statistics. So in this paper, we adopt Bayesian and non-Bayesian approaches for the estimation of CV under type-II censored data from extension exponential distribution [EED]. The point and interval estimate of the CV are obtained for each of the maximum likelihood and parametric bootstrap techniques. Also the Bayesian approach with the help of MCMC method is presented. A real data set is presented and analyzed, hence the obtained results are used to assess the obtained theoretical results.

Keywords

• coefficient of variation
• extension exponential distribution
• type-ii censoring scheme
• bayesian estimation
• bootstrap confidence interval
• maximum likelihood estimation
• mcmc
• 02.50.ga
• 02.50.ng
• 02.50.tt