Abstract

This paper describes some proficient estimation procedures in the presence of multi-auxiliary variables to enhance the precision of estimates in two-occasion rotation sampling. Utilizing information on several auxiliary variables, which are considered to be a positive correlation with the study variables on both occasions, we have suggested some better estimation procedures. The behaviors of the proposed estimation strategies have been examined along with the discussion of optimum replacement strategies, and the results obtained in these estimation procedures are demonstrated numerically through empirical and simulation studies, which present the supremacy in efficiencies of the proposed estimation procedures over the sample mean estimator, natural successive sampling estimator and recently developed estimator.

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