Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1147164 | Journal of Multivariate Analysis | 2009 | 14 Pages |
Abstract
A general depth measure, based on the use of one-dimensional linear continuous projections, is proposed. The applicability of this idea in different statistical setups (including inference in functional data analysis, image analysis and classification) is discussed. A special emphasis is made on the possible usefulness of this method in some statistical problems where the data are elements of a Banach space.The asymptotic properties of the empirical approximation of the proposed depth measure are investigated. In particular, its asymptotic distribution is obtained through UU-statistics techniques. The practical aspects of these ideas are discussed through a small simulation study and a real-data example.
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Antonio Cuevas, Ricardo Fraiman,