Robust Difference and Ratio Type Estimators in Presence of Correlated Measurement Errors Under Ranked Set Sampling

In survey sampling, the problem of correlated measurement errors (CMEs) was initially addressed using conventional estimators under simple random sampling (SRS) and ranked set sampling (RSS). To evaluate the impacts of CMEs, this study proposes some robust difference and ratio types of estimators using RSS methodology. The statistical properties like bias and mean square error are derived up to a first-order approximation. An extensive simulation study is performed, and the results are obtained, which exhibit the robustness of the proposed estimators compared to their conventional counterparts. AMS Subject Classification: MSC2020:62D05