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Asymptotic spectrum of weighted sample covariance: another proof of spectrum convergence

arXiv 2410.14408 ↗First posted 18 Oct 2024math.ST math.PR stat.MLcited by 0

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Abstract (arXiv)

We propose another proof of the high dimensional spectrum convergence of the weighted sample covariance, more concise and self-sufficient but with stronger, but reasonable assumptions. We explain and illustrates this theorem for different weight distributions and show how the spectrum behaves in finite samples with heavy tails. The general purpose is to provide a detailed introduction to the high dimensional spectrum of weighted sample covariance.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 26 references that are in the map. First posted on arXiv 18 Oct 2024.

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References · 2

  1. 2015An Overview on the Estimation of Large Covariance and Precision Matricescited by 21
  2. 2018User-Friendly Covariance Estimation for Heavy-Tailed Distributionscited by 16

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