Large sample properties and asymptotic interval estimation of maximum likelihood estimation of population mean in exponential distribution under optimal ranked set sampling design

This paper investigates the large sample property and asymptotic interval estimation of maximum likelihood estimation (MLE) of population mean in exponential distribution under quasi-sufficient complete statistic ranked set sampling (RSS). In order to improve the effciency of statistical inference, a Fisher information maximization RSS design is proposed, and the large sample property and asymptotic interval estimation of maximum likelihood estimation of population mean in exponential distribution is studied under this design. The numerical results show that the precision of the quasi-sufficient complete statistic RSS asymptotic interval estimation and the Fisher information maximization RSS asymptotic interval estimation are higher than RSS asymptotic interval estimation. The precision of the Fisher information maximization RSS asymptotic interval estimation is higher than the quasi-sufficient complete statistic RSS asymptotic interval estimation.