An Innovative Class of Chain Ratio-Type Estimators Using Auxiliary Information in Sample Survey

Khalid Ul Islam Rather and Tanveer Ahmad Tarray

In survey sampling, the use of auxiliary information at the estimation stage has been discussed by various statisticians to improve the efficiency of their formulated estimators for estimating the population mean. The crux of this study was to propose some modified and improved compromised ratio type estimators to estimate the population mean of the study variate using the information on different parameters. The properties of the suggested estimation procedures have been examined. It has been shown that the proposed class of estimators is better than the usual unbiased estimator, ratio estimator under some realistic conditions. The study has been performed to show that the proposed class of estimators gives better results in comparison to some of the existing estimators. Suitable recommendations are made to the survey practitioners.

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