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arXiv · 2410.14413

WeSpeR: Computing non-linear shrinkage formulas for the weighted sample covariance

Benoit Oriol
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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 \textit{WeSpeR} algorithm and significantly speed up non-linear shrinkage in dimension higher than $1000$. Empirical tests confirm the good properties of the \textit{WeSpeR} algorithm. We provide the implementation in PyTorch for it.

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Benoit Oriol. 2024-10-18. WeSpeR: Computing non-linear shrinkage formulas for the weighted sample covariance. https://arxiv.org/abs/2410.14413

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