Study of A One Parameter Class of Ratio Cum Product Type Compromised Imputation Technique in Survey Sampling
In this paper, a one parameter class of ratio-cum-product type compromised imputation technique and corresponding point estimator has been proposed and also the expressions for bias and mean square error are derived. Further, empirical studies are given to compare the performance of the estimator with other existing estimators such as mean method of imputation, ratio method of imputation, compromised method of imputation and Ahmed methods of imputation. It has been found that the ratio-cum-product estimator is more efficient than other existing methods of imputation.
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