Parametric estimation for the scale parameter for scale distributions using moving extremes ranked set sampling

A modification of ranked set sampling (RSS) called moving extremes ranked set sampling (MERSS) is considered for the estimation of the scale parameter of scale distributions. A maximum likelihood estimator (MLE) is studied and its properties are obtained. We prove the MLE is an equivariant estimator under scale transformation. In order to give more insight into the performance of MERSS with respect to (w.r.t.) simple random sampling (SRS), the asymptotic efficiency of the MLE using MERSS w.r.t. that using SRS is computed for some usual scale distributions. The relative results show that the MLE using MERSS can be real competitors to the MLE using SRS, when the same sample size is used.