Eigenvalue density of empirical covariance matrix for correlated samples

Simple item page
dc.creatorBurda, Z.
dc.creatorJurkiewicz, J.
dc.creatorWaclaw, B.
dc.date2005-08-19
dc.date.accessioned2026-07-07T12:07:05Z
dc.date.available2026-07-07T12:07:05Z
dc.descriptionWe describe a method to determine the eigenvalue density of empirical covariance matrix in the presence of correlations between samples. This is a straightforward generalization of the method developed earlier by the authors for uncorrelated samples. The method allows for exact determination of the experimental spectrum for a given covariance matrix and given correlations between samples in the limit of large N and N/T=r=const with N being the number of degrees of freedom and T being the number of samples. We discuss the effect of correlations on several examples.
dc.description12 pages, 5 figures, to appear in Acta Phys. Pol. B (Proceedings of the conference on `Applications of Random Matrix Theory to Economy and Other Complex Systems', May 25-28, 2005, Cracow, Poland
dc.identifierhttps://arxiv.org/abs/cond-mat/0508451
dc.identifierhttp://arxiv.org/abs/cond-mat/0508451
dc.identifierActa Phys. Pol. B36, 2641 (2005)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/208850
dc.subjectStatistical Mechanics
dc.subjectOther Condensed Matter
dc.subjectStatistical Finance
dc.titleEigenvalue density of empirical covariance matrix for correlated samples
dc.typetext

Files

Collections

arXiv