Comments on a result of Yin, Bai, and Krishnaiah for large dimensional multivariate F matrices

A theorem in [1] shows that the smallest eigenvalue of a class of large dimensional sample covariance matrices stays almost surely bounded away from zero. The theorem assumes a certain restriction on the class of matrices. With slight modifications of the proof in op cit, it is shown here that the theorem is true for all relevant matrices.

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Year of publication:	1984
Authors:	Silverstein, Jack W.
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 15.1984, 3, p. 408-409
Publisher:	Elsevier
Keywords:	large dimensional sample covariance matrices smallest eigen-value

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005221621