On the distribution of the left singular vectors of a random matrix and its applications

DOI10.1016/j.spl.2008.01.097zbMath1146.62011OpenAlexW2032789392MaRDI QIDQ951163

Ruth M. Pfeiffer, Efstathia Bura

Publication date: 30 October 2008

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2008.01.097

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Random matrices (algebraic aspects) (15B52)

Related Items (11)

Sufficient dimension reduction via principal L\(q\) support vector machine ⋮ Subspace-based fault detection robust to changes in the noise covariances ⋮ On sliced inverse regression with missing values ⋮ Principal quantile regression for sufficient dimension reduction with heteroscedasticity ⋮ Dimension estimation in sufficient dimension reduction: a unifying approach ⋮ Principal support vector machines for linear and nonlinear sufficient dimension reduction ⋮ Principal weighted logistic regression for sufficient dimension reduction in binary classification ⋮ Rate-optimal perturbation bounds for singular subspaces with applications to high-dimensional statistics ⋮ Using adaptively weighted large margin classifiers for robust sufficient dimension reduction ⋮ A note on rank reduction in sparse multivariate regression ⋮ Singular Vector Perturbation Under Gaussian Noise

Cites Work

• Asymptotic inference for eigenvectors
• Sliced Inverse Regression for Dimension Reduction
• Asymptotic study of eigenelements of a sequence of random selfadjoint operators
• Generalized Inverses, Wald's Method, and the Construction of Chi-Squared Tests of Fit
• Extending Sliced Inverse Regression
• Dimension Reduction in Binary Response Regression
• Comment
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