Shrinkage Coefficient Estimation for Regularized Tyler’s M–Estimator: A Leave One Out Approach
Author:
Affiliation:
1. Intel Corp. Chandler,AZ,85226
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10160228/10160229/10161652.pdf?arnumber=10161652
Reference28 articles.
1. Regularized Covariance Matrix Estimation in Complex Elliptically Symmetric Distributions Using the Expected Likelihood Approach—Part 2: The Under-Sampled Case
2. Regularized Covariance Matrix Estimation in Complex Elliptically Symmetric Distributions Using the Expected Likelihood Approach— Part 1: The Over-Sampled Case
3. Shrinking the eigenvalues of M-estimators of covariance matrix;ollila;IEEE Transactions on Signal Processing,2021
4. Optimal Shrinkage Covariance Matrix Estimation Under Random Sampling From Elliptical Distributions
5. Automatic diagonal loading for Tyler’s robust covariance estimator;zhang;2016 IEEE Statistical Signal Processing Workshop (SSP),2016
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