Quantiles for finite and infinite dimensional data

DOI10.1016/j.jmva.2012.01.016zbMath1238.62063OpenAlexW2002680350WikidataQ60540697 ScholiaQ60540697MaRDI QIDQ414539

Ricardo Fraiman, Beatriz Pateiro-López

Publication date: 11 May 2012

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2012.01.016

zbMATH Keywords

Hilbert spacehigh dimensional multivariate dataprincipal quantile directionsquantiles for functional data

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Asymptotic properties of nonparametric inference (62G20) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Applications of functional analysis in probability theory and statistics (46N30) Graphical methods in statistics (62A09)

Related Items

Reduced form vector directional quantiles, Resistant estimates for high dimensional and functional data based on random projections, Marginal M-quantile regression for multivariate dependent data, On the estimation of extreme directional multivariate quantiles, A partial overview of the theory of statistics with functional data, Principal component analysis in an asymmetric norm, Best approach direction for spherical random variables, A directional multivariate value at risk, The spatial distribution in infinite dimensional spaces and related quantiles and depths, Multivariate Quantile Impulse Response Functions, Flexible quantile contour estimation for multivariate functional data: beyond convexity

Uses Software

• R
• Rainbow
• fda (R)
• fda.usc

Cites Work

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