[KSCI] Korea Science Citation Index Service

QUANTILE ESTIMATION IN SUCCESSIVE SAMPLING

Singh, Housila P. (School of Studies in Statistics, Vikram University)
Tailor, Ritesh (School of Studies in Statistics, Vikram University)
Singh, Sarjinder (Department of Statistics, St. Cloud State University)
Kim, Jong-Min (Statistics Discipline, Division of Science and Mathematics, University of Minnesota at Morris)

Publication Information

Journal of the Korean Statistical Society / v.36, no.4, 2007 , pp. 543-556 More about this Journal

Abstract

In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion of the sample on the second occasion. The approximate variance formulae of the suggested estimators have been obtained. Optimal matching fraction is discussed. A simulation study is carried out in order to compare the three estimators and direct estimator. It is found that the performance of the regression-type estimator is the best among all the estimators discussed here.

Keywords

Auxiliary information; finite population quantile; partial replacement; successive sampling;

Citations & Related Records

Times Cited By Web Of Science : 1 (Related Records In Web of Science)

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