On the use of ranked set sampling for estimating super-population total: Gamma population model

The application of superpopulation models to estimate population parameters is an advantageous practice when recognizing the relationship between the study variable and one or more auxiliary variables is a simple matter. This paper aims to estimate the nite population total under Ranked Set Sampling Without Replacement (RSSWOR) employing the model relationship, especially Gamma Population Model (GPM), between the study and auxiliary variables. Behavior of the proposed estimator, in terms of relative eciency, is studied in the case of a constant through Monte Carle experiment. The simulation study demonstrates the superiority of the proposed estimator to existing estimators under the same model. The sampling procedure, in particular, facilitates collecting data from a continuous production process.