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THE OPTIMAL RANKED-SET SAMPLING SCHEME FOR INFERENCE ON POPULATION QUANTILES
Vol. 11, No. 1 (January 2001), pp. 23-37
Published by: Institute of Statistical Science, Academia Sinica
Stable URL: http://www.jstor.org/stable/24306807
Page Count: 15
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In this article, we consider the design of unbalanced ranked-set sampling in order to achieve certain optimality for inference on quantiles. We first derive the asymptotic properties of the unbalanced ranked-set sample quantiles for any unbalanced ranked-set sampling scheme. Then these properties are employed to develop a methodology for determining optimal ranked-set sampling schemes. In the case of inference on a single quantile, the optimal scheme results in an estimator of the quantile which is asymptotically unbiased and with minimum variance among all ranked-set sample (balanced or unbalanced) quantiles. The striking feature of the methodology is that it is distribution-free. The optimal schemes for inference on certain quantiles are computed. Some simulation studies are reported.
Statistica Sinica © 2001 Institute of Statistical Science, Academia Sinica