Component-wise outlier detection methods for robustifying multivariate functional samples

DOI10.1007/s00362-017-0953-1zbMath1435.62194OpenAlexW2759710611MaRDI QIDQ2306882

Anna Maria Paganoni, Francesca Ieva

Publication date: 27 March 2020

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-017-0953-1

zbMATH Keywords

robustnessoutlier detectionmultivariate functional samples

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Functional data analysis (62R10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Statistics of extreme values; tail inference (62G32)

Related Items (1)

Integrated Depths for Partially Observed Functional Data

Uses Software

• R
• Rainbow
• fda (R)
• roahd
• FUNTA
• rFUNTA

Cites Work

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• Dispersion operators and resistant second-order functional data analysis
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• DD-Classifier: Nonparametric Classification Procedure Based onDD-Plot
• Depth Measures for Multivariate Functional Data
• Multivariate Functional Halfspace Depth
• On the Concept of Depth for Functional Data

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