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Diagonal Attenuation: A Finite-Sample Correction for PCA

Sun, Qiang
arXiv (All) · Papers
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machine-learningmethodologystatistics-theory
Principal component analysis (PCA) can rotate away from its population target when a covariance matrix is estimated from limited data. We introduce diagonal attenuation, which preserves sample cross-covariances while reducing coordinatewise sample variances. The method is revealed exactly by averagi
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