Abstract
Five notions of data depth are considered. They are mostly designed for functional data but they can be also adapted to the standard multivariate case. The performance of these depth notions, when used as auxiliary tools in estimation and classification, is checked through a Monte Carlo study.
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Research partially supported by Spanish grants MTM2004-00098 (A. Cuevas and R. Fraiman) and MTM2005-00820 (M. Febrero).
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Cuevas, A., Febrero, M. & Fraiman, R. Robust estimation and classification for functional data via projection-based depth notions. Computational Statistics 22, 481–496 (2007). https://doi.org/10.1007/s00180-007-0053-0
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DOI: https://doi.org/10.1007/s00180-007-0053-0