Shrinkage estimation of high dimensional covariance matrices

@article{Chen2009ShrinkageEO,
  title={Shrinkage estimation of high dimensional covariance matrices},
  author={Yilun Chen and Ami Wiesel and Alfred O. Hero},
  journal={2009 IEEE International Conference on Acoustics, Speech and Signal Processing},
  year={2009},
  pages={2937-2940}
}
We address covariance estimation under mean-squared loss in the Gaussian setting. Specifically, we consider shrinkage methods which are suitable for high dimensional problems with small number of samples (large p small n). First, we improve on the Ledoit-Wolf (LW) method by conditioning on a sufficient statistic via the Rao-Blackwell theorem, obtaining a new estimator RBLW whose mean-squared error dominates the LW under Gaussian model. Second, to further reduce the estimation error, we propose… CONTINUE READING
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