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M-estimators of location for functional data

Journal Contribution - Journal Article

© 2018 ISI/BS. M-estimators of location are widely used robust estimators of the center of univariate or multivariate real-valued data. This paper aims to study M-estimates of location in the framework of functional data analysis. To this end, recent developments for robust nonparametric density estimation by means of M-estimators are considered. These results can also be applied in the context of functional data analysis and allow to state conditions for the existence and uniqueness of location M-estimates in this setting. Properties of these functional M-estimators are investigated. In particular, their consistency is shown and robustness is studied by means of their breakdown point and their influence function. The finite-sample performance of the M-estimators is explored by simulation. The M-estimators are also empirically compared to trimmed means for functional data.
Journal: Bernoulli
ISSN: 1350-7265
Issue: 3
Volume: 24
Pages: 2328 - 2357
Publication year:2018
BOF-keylabel:yes
IOF-keylabel:yes
BOF-publication weight:1
CSS-citation score:1
Authors:International
Authors from:Higher Education
Accessibility:Open