Robust sparse covariance estimation by thresholding Tyler's M-estimator
From MaRDI portal
Publication:2176609
DOI10.1214/18-AOS1793zbMath1439.62123arXiv1706.08020MaRDI QIDQ2176609
Boaz Nadler, Gilad Lerman, John Goes
Publication date: 5 May 2020
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1706.08020
thresholdingsparsityspectral normelliptical distributioncovariance matrix estimationTyler's M-estimator
Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35) Inference from stochastic processes and spectral analysis (62M15)
Related Items
An overview of heavy-tail extensions of multivariate Gaussian distribution and their relations, Robust sparse covariance estimation by thresholding Tyler's M-estimator, Robust Shape Matrix Estimation for High-Dimensional Compositional Data with Application to Microbial Inter-Taxa Analysis, Tyler's and Maronna's M-estimators: non-asymptotic concentration results, Robust Covariance Matrix Estimation for High-Dimensional Compositional Data with Application to Sales Data Analysis, Covariance Model with General Linear Structure and Divergent Parameters, Rejoinder to “A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression”
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Marčenko-Pastur law for Tyler's M-estimator
- Large dimensional analysis and optimization of robust shrinkage covariance matrix estimators
- Optimal rates of convergence for sparse covariance matrix estimation
- Hanson-Wright inequality and sub-Gaussian concentration
- Second order statistics of robust estimators of scatter. Application to GLRT detection for elliptical signals
- New algorithms for \(M\)-estimation of multivariate scatter and location
- A generalization of Tyler's M-estimators to the case of incomplete data
- Covariance regularization by thresholding
- Operator norm consistent estimation of large-dimensional sparse covariance matrices
- Sparsistency and rates of convergence in large covariance matrix estimation
- A distribution-free M-estimator of multivariate scatter
- On the theory of elliptically contoured distributions
- Redescending \(M\)-estimates of multivariate location and scatter
- Robust m-estimators of multivariate location and scatter
- On Tyler's \(M\)-functional of scatter in high dimension
- Concentration of the spectral measure for large matrices
- The sample covariance is not efficient for elliptical distributions
- Robust and efficient estimation of multivariate scatter and location
- Robust covariance and scatter matrix estimation under Huber's contamination model
- Robust sparse covariance estimation by thresholding Tyler's M-estimator
- \(M\)-functionals of multivariate scatter
- The random matrix regime of Maronna's M-estimator with elliptically distributed samples
- Symmetrised M-estimators of multivariate scatter
- Robust Estimates of Covariance Matrices in the Large Dimensional Regime
- Adaptive Thresholding for Sparse Covariance Matrix Estimation
- A cautionary note on robust covariance plug-in methods
- Statistical analysis for the angular central Gaussian distribution on the sphere
- Robust Shrinkage Estimation of High-Dimensional Covariance Matrices
- Unified Framework to Regularized Covariance Estimation in Scaled Gaussian Models
- Regularized Tyler's Scatter Estimator: Existence, Uniqueness, and Algorithms
- Tyler's Covariance Matrix Estimator in Elliptical Models With Convex Structure
- Generalized Robust Shrinkage Estimator and Its Application to STAP Detection Problem
- Regularized <formula formulatype="inline"><tex Notation="TeX">$M$</tex> </formula>-Estimators of Scatter Matrix
- Large Dimensional Analysis of Robust M-Estimators of Covariance With Outliers
- Robust Estimation of Structured Covariance Matrix for Heavy-Tailed Elliptical Distributions
- Generalized Thresholding of Large Covariance Matrices
- Robust estimation of high-dimensional covariance and precision matrices
- Structured Robust Covariance Estimation
- Robust Statistics
- Estimating structured high-dimensional covariance and precision matrices: optimal rates and adaptive estimation
