Resampling-based Classification Using Depth for Functional Curves

DOI10.1080/03610918.2014.944652zbMath1403.62115OpenAlexW2068647304MaRDI QIDQ2828715

Amy M. Kwon, Andrew L. Cheng, Ming Ou-Yang

Publication date: 26 October 2016

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2014.944652

zbMATH Keywords

classificationbootstrapjackknifefunctional depthfunctional curves

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric statistical resampling methods (62G09)

Related Items (1)

Robust multivariate functional discriminant coordinates

Cites Work

• On a notion of data depth based on random simplices
• Robust estimation and classification for functional data via projection-based depth notions
• On depth measures and dual statistics. A methodology for dealing with general data
• The random Tukey depth
• Descriptive statistics for multivariate distributions
• Bootstrap methods: another look at the jackknife
• Nonparametric comparison of several regression functions: Exact and asymptotic theory
• Multivariate analysis by data depth: Descriptive statistics, graphics and inference. (With discussions and rejoinder)
• Applied functional data analysis. Methods and case studies
• Trimmed means for functional data
• Penalized discriminant analysis
• Spatial depth-based classification for functional data
• Functional Linear Discriminant Analysis for Irregularly Sampled Curves
• Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods
• A similarity analysis of curves
• On the Concept of Depth for Functional Data
• Robustness and Complex Data Structures

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