On the Improvement of Multivariate Ratio Method of Estimation in Sample Surveys by Calibration Weightings
Asian Journal of Probability and Statistics · pp. 1–12 · Published 12 Dec 2020
10.9734/ajpas/2020/v10i130236Abstract
The most challenging limitation of the ratio estimation is that of deriving variance estimator that admits more than two auxiliary variables. This paper introduces a new calibration weights that prompt the formulation of a multivariate ratio estimator by the calibration tuning parameter subject to a pooled-calibration constraint. Analytical framework for deriving variance estimator that admits as many auxiliary variables as desired is developed. The efficiency gains of the proposed estimator vis-a-vis the Generalized Regression (GREG) Estimator are studied through simulation. Simulation results proved the dominance of the new proposals over existing ones.
Cited by 2
Etebong P. Clement, A. Anieting · International Journal of Statistical Sciences · 2024
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