Efficient R-Estimation of Principal and Common Principal Components

DOI10.1080/01621459.2014.880057zbMath1368.62160OpenAlexW2098235563MaRDI QIDQ4975560

Marc Hallin, Thomas Verdebout, Davy Paindaveine

Publication date: 7 August 2017

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/172802/3/RestimPC.pdf

zbMATH Keywords

robustnessranksuniform local asymptotic normalityelliptical densities

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (12)

Efficient ANOVA for directional data ⋮ The fixed effects PCA model in a common principal component environment ⋮ Testing for principal component directions under weak identifiability ⋮ A class of optimization problems motivated by rank estimators in robust regression ⋮ Semiparametric error-correction models for cointegration with trends: pseudo-Gaussian and optimal rank-based tests of the cointegration rank ⋮ Principal component analysis: a review and recent developments ⋮ Preliminary Multiple-Test Estimation, With Applications to k-Sample Covariance Estimation ⋮ On testing the equality of latent roots of scatter matrices under ellipticity ⋮ Optimal tests for elliptical symmetry: specified and unspecified location ⋮ ECA: High-Dimensional Elliptical Component Analysis in Non-Gaussian Distributions ⋮ Distribution and quantile functions, ranks and signs in dimension \(d\): a measure transportation approach ⋮ Rank-based testing for semiparametric VAR models: a measure transportation approach

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