On the Improvement of Multivariate Ratio Method of Estimation in Sample Surveys by Calibration Weigh

Deriving a variance estimator that accepts more than two auxiliary variables is the most difficult limitation of ratio estimation. The calibration tuning parameter is subjected to a pooled-calibration constraint in this paper, which prompts the creation of a multivariate ratio estimator using the calibration weights. The development of an analytical framework for producing a variance estimator that accepts as many auxiliary variables as desired. Simulation is used to investigate the efficiency improvements of the proposed estimator over the Generalized Regression (GREG) Estimator. The new suggestions' supremacy over previous ones was demonstrated by simulation results.

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