Semicircle law of Tyler’s M-estimator for scatter
This paper analyzes the spectral properties of Tyler’s M-estimator for scatter Tn,d. It is shown that if a multivariate sample stems from a generalized spherically distributed population and the sample size n and the dimension d both go to infinity while d/n→0, then the empirical spectral distribution of n/d(Tn,d−Id), Id being the identity, converges in probability to the semicircle law. In contrast to that of the sample covariance matrix, this convergence does not necessarily require the sample vectors to be componentwise independent. Further, moments of the generalized spherical population do not have to exist.
Volume (Year): 82 (2012)
Issue (Month): 5 ()
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Frahm, Gabriel, 2009. "Asymptotic distributions of robust shape matrices and scales," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1329-1337, August.
- Frahm, Gabriel & Jaekel, Uwe, 2009. "A generalization of Tyler's M-estimators to the case of incomplete data," Discussion Papers in Econometrics and Statistics 3/07, University of Cologne, Institute of Econometrics and Statistics.
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