A note on universality of the distribution of the largest eigenvalues in certain sample covariance matrices
arXiv:math/0104113
Abstract
Recently Johansson and Johnstone proved that the distribution of the (properly rescaled) largest principal component of the complex (real) Wishart matrix $ X^* \* X (X^t \*X) $ converges to the Tracy-Widom law as (the dimensions of ) tend to in some ratio We extend these results in two directions. First of all, we prove that the joint distribution of the first, second, third, etc. eigenvalues of a Wishart matrix converges (after a proper rescaling) to the Tracy-Widom distribution. Second of all, we explain how the combinatorial machinery developed for Wigner matrices allows to extend the results by Johansson and Johnstone to the case of with non-Gaussian entries, provided We also prove that $ λ_{max} \leq (n^{1/2}+p^{1/2})^2 +O(p^{1/2}\*\log(p)) $ (a.e.) for general
This is a preliminary version. Minor misprints are corrected
References in corpus (1)
Cited by in corpus (13)
- Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects
- OptShrink: An algorithm for improved low-rank signal matrix denoising by optimal, data-driven singular value shrinkage
- Universality of covariance matrices
- Universality for the largest eigenvalue of sample covariance matrices with general population
- The Wasteland of Random Supergravities
- Edge universality of correlation matrices
- The largest eigenvalues of sample covariance matrices for a spiked population: diagonal case
- Fast approach to the Tracy-Widom law at the edge of GOE and GUE
- On the probability that all eigenvalues of Gaussian, Wishart, and double Wishart random matrices lie within an interval
- Application of Random Matrix Theory to Multivariate Statistics
- Some results on random circulant matrices
- On the convergence of the extremal eigenvalues of empirical covariance matrices with dependence
- Spectral gene set enrichment (SGSE)