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Pmc-optimal nonparametric quantile estimator
Authors:Ryszard Zieliński
Affiliation:Institute of Mathematics, Polish Academy of Sciences
Abstract:According to Pitman's Measure of Closeness, if T1and T2are two estimators of a real parameter $[d], then T1is better than T2if Po[d]{T1-o[d] < T2-0[d]} > 1/2 for all 0[d]. It may however happen that while T1is better than T2and T2is better than T3, T3is better than T1. Given q ? (0,1) and a sample X1, X2, ..., Xnfrom an unknown F ? F, an estimator T* = T*(X1,X2...Xn)of the q-th quantile of the distribution F is constructed such that PF{F(T*)-q <[d] F(T)-q} >[d] 1/2 for all F?F and for all T€T, where F is a nonparametric family of distributions and T is a class of estimators. It is shown that T* =Xj:n'for a suitably chosen jth order statistic.
Keywords:Quantile estimators  Nonparametric model  Optimal estimation  Equivariant estimators  PMC (Pitman's Measure of Closeness)
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