WeSpeR: Computing non-linear shrinkage formulas for the weighted sample covariance
Abstract
We address the issue of computing the non-linear shrinkage formulas for the weighted sample covariance in high dimension. We use theoretical properties of the asymptotic sample spectrum in order to derive the WeSpeR algorithm and significantly speed up non-linear shrinkage in dimension higher than 1000. Empirical tests confirm the good properties of the WeSpeR algorithm. We provide the implementation in PyTorch for it.
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