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Bootstrap Techniques for Estimation of Variance under Ranked Set Sampling Framework
by
T. Ahmad
Indian Agricultural Statistics Research Institute, New Delhi-110012, India
Coauthors: P.M.Sahoo, Anil Rai and G.K.Jha
In experimental settings where measuring an observation is expensive, but ranking a small sub set of observations is relatively easy, ranked set sampling(RSS) can be used to increase the precision of the estimators. The majority of research for RSS has been concerned with estimating the mean. Estimating the population variance in case of ranked set sampling has been found to be cumbersome. Therefore, in this paper some bootstrap techniques have been proposed for estimation of variance under ranked set sampling framework. Further, a comparison has been made between proposed and usual variance estimators using ranked set samples.
Date received: November 30, 2004
Copyright © 2004 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # caph-98.