High Dimensional Covariance Matrix Estimation
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High-dimensional data appear in many fields, and their analysis has become increasingly important in modern statistics. However, it has long been observed that
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This paper proposes a novel shrinkage estimator for high-dimensional covariance matrices by extending the Oracle Approximating Shrinkage (OAS) of Chen et al. (2
