Quadratic shrinkage for large covariance matrices
Author:
Affiliation:
1. Department of Economics, University of Zurich, 8032 Zurich, Switzerland
Publisher
Bernoulli Society for Mathematical Statistics and Probability
Subject
Statistics and Probability
Reference69 articles.
1. Abrahamsson, R., Selen, Y. and Stoica, P. (2007). Enhanced covariance matrix estimators in adaptive beamforming. In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing – ICASSP 2007 II 969–972.
2. Bai, Z.D. and Silverstein, J.W. (1998). No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices. Ann. Probab. 26 316–345. 10.1214/aop/1022855421
3. Bickel, P.J. and Levina, E. (2008a). Covariance regularization by thresholding. Ann. Statist. 36 2577–2604. 10.1214/08-AOS600
4. Bickel, P.J. and Levina, E. (2008b). Regularized estimation of large covariance matrices. Ann. Statist. 36 199–227. 10.1214/009053607000000758
5. Bodnar, T., Gupta, A.K. and Parolya, N. (2016). Direct shrinkage estimation of large dimensional precision matrix. J. Multivariate Anal. 146 223–236. 10.1016/j.jmva.2015.09.010
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