Depth-based inference for functional data

Authors:
Sara López-Pintado;Juan Romo
Affiliations:
Department of Statistics, Universidad Carlos III de Madrid, C/Madrid, 126, 28903 Getafe, Madrid, Spain;Department of Statistics, Universidad Carlos III de Madrid, C/Madrid, 126, 28903 Getafe, Madrid, Spain
Venue:
Computational Statistics & Data Analysis
Year:
2007

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Abstract

Robust inference tools for functional data are proposed. They are based on the notion of depth for curves. The ideas of trimmed regions, contours and central regions are extended to functions and their structural properties and asymptotic behavior are studied. Next, a scale curve is introduced to describe dispersion in a sample of functions. The computational burden of these techniques is not heavy, so they are also adequate to analyze high-dimensional data. These inferential methods are applied to several real data sets.