Abstract #301620

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JSM 2003 Abstract #301620
Activity Number: 295
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #301620
Title: Depth-based Inference for Functional Data
Author(s): Juan Romo*+ and Sara Lopez-Pintado
Companies: Universidad Carlos III De Madrid and Universidad Carlos III De Madrid
Address: Madrid, 126, Getafe, Madrid, 28903, Spain
Keywords: functional data ; data depth ; trimmed regions
Abstract:

The idea of statistical depth is useful to analyze multivariate data, and recently it has been extended to functional observations. We explore the applications of a new definition of depth when the observations are curves. The natural center-outward order of the sample induced by a depth allows to construct trimmed regions and contours. We prove that these regions verify essentially all the desirable properties established by Zuo and Serfling (2000). They help to visualize characteristics as the populational dispersion. Also a depth-based Wilcoxon rank test can be introduced. We apply all these techniques to several real datasets.

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