https://cdn.jwplayer.com/libraries/kxatZa2V.js CIRM - Videos & books Library - Asymptotic theory for the sample covariance matrix of a heavy-tailed multivariate time series
En poursuivant votre navigation sur ce site, vous acceptez l'utilisation d'un simple cookie d'identification. Aucune autre exploitation n'est faite de ce cookie. OK
1

Asymptotic theory for the sample covariance matrix of a heavy-tailed multivariate time series

Sélection Signaler une erreur
Post-edited
Auteurs : Mikosch, Thomas (Auteur de la Conférence)
CIRM (Editeur )

Loading the player...
PCA sample covariance matrix Tracy-Widom distribution regularly varying linear process asymptotic theory for largest eigen values point process of eigen values proof of convergence of largest eigen values

Résumé : We give an asymptotic theory for the eigenvalues of the sample covariance matrix of a multivariate time series. The time series constitutes a linear process across time and between components. The input noise of the linear process has regularly varying tails with index $\alpha \in \left ( 0,4 \right )$; in particular, the time series has infinite fourth moment. We derive the limiting behavior for the largest eigenvalues of the sample covariance matrix and show point process convergence of the normalized eigenvalues. The limiting process has an explicit form involving points of a Poisson process and eigenvalues of a non-negative denite matrix. Based on this convergence we derive limit theory for a host of other continuous functionals of the eigenvalues, including the joint convergence of the largest eigenvalues, the joint convergence of the largest eigenvalue and the trace of the sample covariance matrix, and the ratio of the largest eigenvalue to their sum. This is joint work with Richard A. Davis (Columbia NY) and Oliver Pfaffel (Munich).

Codes MSC :
60G55 - Point processes
62G32 - Statistics of extreme values; tail inference

    Informations sur la Vidéo

    Réalisateur : Hennenfent, Guillaume
    Langue : Anglais
    Date de publication : 28/07/14
    Date de captation : 16/07/14
    Sous collection : Research talks
    arXiv category : Probability ; Statistics Theory
    Domaine : Probability & Statistics
    Format : QuickTime (.mov) Durée : 00:55:53
    Audience : Researchers
    Download : https://videos.cirm-math.fr/2014-07-16_Mikosch.mp4

Informations sur la Rencontre

Nom de la rencontre : Extreme value theory and laws of rare events / Théorie des valeurs extrêmes et lois des évènements rares
Organisateurs de la rencontre : Freitas, Ana Cristina ; Freitas, Jorge ; Todd, Michael J. ; Vaienti, Sandro
Dates : 14/07/14 - 18/07/14
Année de la rencontre : 2014
URL Congrès : http://www.mcs.st-and.ac.uk/~miket/CIRM_...

Données de citation

DOI : 10.24350/CIRM.V.18538803
Citer cette vidéo: Mikosch, Thomas (2014). Asymptotic theory for the sample covariance matrix of a heavy-tailed multivariate time series. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.18538803
URI : http://dx.doi.org/10.24350/CIRM.V.18538803

Bibliographie



Sélection Signaler une erreur