Rates of Bootstrap Approximation for Eigenvalues in High-Dimensional PCA

DOI10.5705/ss.202021.0158arXiv2104.07328WikidataQ114013791 ScholiaQ114013791MaRDI QIDQ6069877

Publication date: 17 November 2023

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2104.07328

zbMATH Keywords

bootstrap high-dimensional statistics covariance matrices principal components analysis

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

A bootstrap method for spectral statistics in high-dimensional elliptical models

Cites Work

Unnamed Item
Unnamed Item
Nonlinear shrinkage estimation of large-dimensional covariance matrices
High-dimensional covariance matrix estimation with missing observations
Random design analysis of ridge regression
Normal approximation and concentration of spectral projectors of sample covariance
Tie-respecting bootstrap methods for estimating distributions of sets and functions of eigenvalues
Spectral analysis of large dimensional random matrices
Bootstrap tests and confidence regions for functions of a covariance matrix
Correction to: Bootstrap tests and confidence regions for functions of a covariance matrix
On Wielandt's inequality and its application to the asymptotic distribution of the eigenvalues of a random symmetric matrix
Normalizing transformations and bootstrap confidence intervals
On nondifferentiable functions and the bootstrap
Bootstrap confidence intervals. With comments and a rejoinder by the authors
On Gaussian comparison inequality and its application to spectral analysis of large random matrices
High-dimensional asymptotics of prediction: ridge regression and classification
Principal component analysis.
Bootstrapping the operator norm in high dimensions: error estimation for covariance matrices and sketching
Efficient estimation of linear functionals of principal components
Bootstrapping max statistics in high dimensions: near-parametric rates under weak variance decay and application to functional and multinomial data
Bootstrap confidence sets for spectral projectors of sample covariance
On the sample covariance matrix estimator of reduced effective rank population matrices, with applications to fPCA
Random Matrix Methods for Wireless Communications
On parameter transformations and interval estimation
Variance stabilization and the bootstrap
High-Dimensional Probability
Bootstrapping spectral statistics in high dimensions
Statistics and Data Analysis for Financial Engineering
Robust Multivariate Analysis
On the number of principal components in high dimensions
High-Dimensional MANOVA Via Bootstrapping and Its Application to Functional and Sparse Count Data

This page was built for publication: Rates of Bootstrap Approximation for Eigenvalues in High-Dimensional PCA