CHAIN REGRESSION-TYPE ESTIMATOR USING MULTIPLE AUXILIARY INFORMATION IN SUCCESSIVE SAMPLING

Housila P. Singh, Manoj Kumar Srivastava, Namita Srivastava, Tanveer A. Tarray, Virendra Singh, and Shivam Dixit ∗ Abstract In successive sampling, the use of auxiliary information for estimation of population mean on current occasion is a well explored area. In the present work, the information on an auxiliary variable, which is available on both the occasions, is used along with the information on the study variable from the previous occasion and the current occasion. Consequently, chain regression-type estimator for estimating the population mean are proposed in two occasions successive sampling. The optimal replacement policy is also discussed. We have also given an empirical study along with pictorial representation to examine the merit of the proposed estimator.