JSM 2003 Online Program

Abstract #300328

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Activity Number:	295
Type:	Contributed
Date/Time:	Tuesday, August 5, 2003 : 2:00 PM to 3:50 PM
Sponsor:	Section on Nonparametric Statistics
Abstract - #300328
Title:	Data Depth Based on Spatial Rank
Author(s):	Yonghong Gao*+
Companies:	University of Missouri, Kansas City
Address:	Dept of Mathematics & Statistics, Kansas City, MO, 64110,
Keywords:	asymptotic distribution ; data depth ; efficiency ; L-estimator ; spatial rank
Abstract:	For a p-dimensional distribution F and a point x, the depth D(x) is introduced, which is a function of the Euclidean norm of the spatial rank of x with respect to F. We show our rank based depth D(x) satisfies some properties one would expect from a notion of data depth. Sample version D_n(x) is uniformly consistent with D(x), and the asymptotic distribution of D_n(x) is discussed. We study the large sample properties of the depth-based L-estimator of the population mean and the simulation study shows that our DL-estimator has good finite sample efficiency.

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