Log-extended exponential-geometric parameters estimation using simple random sampling and moving extremes ranked set sampling

In this paper, estimation of parameters alpha and beta for the log-extended exponential-geometric distribution will be respectively considered in cases when beta is known and when both are unknown. Simple random sampling (SRS) and moving extremes ranked set sampling (MERSS) will be used, and several traditional estimators will be considered. The estimators using MERSS are compared to the corresponding ones using SRS. The numerical results show that the estimators using MERSS are significantly more efficient than the ones using SRS. A real data set is used for illustration.