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

arXiv: https://arxiv.org/abs/2410.14408 · HTML: https://mlsanity.com/paper/2410.14408/

## 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.

## Builds on (most cited first, 2 of 2)

- [An Overview on the Estimation of Large Covariance and Precision Matrices](https://mlsanity.com/paper/1504.02995/) (2015)
- [User-Friendly Covariance Estimation for Heavy-Tailed Distributions](https://mlsanity.com/paper/1811.01520/) (2018)

## 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.