Marčenko-Pastur law for Tyler's M-estimator

DOI10.1016/j.jmva.2016.03.010zbMath1381.62109arXiv1401.3424OpenAlexW2315096753MaRDI QIDQ290712

Teng Zhang, Amit Singer, Xiuyuan Cheng

Publication date: 3 June 2016

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

Full work available at URL: https://arxiv.org/abs/1401.3424

zbMATH Keywords

random matrix theoryrobust statisticscovariance estimation

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Robustness and adaptive procedures (parametric inference) (62F35) Random matrices (algebraic aspects) (15B52)

Related Items (9)

An overview of heavy-tail extensions of multivariate Gaussian distribution and their relations ⋮ Consistency and asymptotic normality of M-estimates of scatter on Grassmann manifolds ⋮ Robust sparse covariance estimation by thresholding Tyler's M-estimator ⋮ Tyler's and Maronna's M-estimators: non-asymptotic concentration results ⋮ Sub-Gaussian estimators of the mean of a random matrix with heavy-tailed entries ⋮ Robust modifications of U-statistics and applications to covariance estimation problems ⋮ User-friendly covariance estimation for heavy-tailed distributions ⋮ Unnamed Item ⋮ A concentration of measure and random matrix approach to large-dimensional robust statistics

Cites Work

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• Large Dimensional Analysis of Robust M-Estimators of Covariance With Outliers
• Robust subspace recovery by Tyler's M-estimator
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