Real and complex analysis, 3rd ed.
Real and complex analysis, 3rd ed.
Analysis of the limiting spectral distribution of large dimensional random matrices
Journal of Multivariate Analysis
Strong convergence of the empirical distribution of eigenvalues of large dimensional random matrices
Journal of Multivariate Analysis
Journal of Multivariate Analysis
Signal detection via spectral theory of large dimensional randommatrices
IEEE Transactions on Signal Processing
Journal of Multivariate Analysis
Large system spectral analysis of covariance matrix estimation
IEEE Transactions on Information Theory
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A derivation of results on the analytic behavior of the limiting spectral distribution of sample covariance matrices of the ''information-plus-noise'' type, as studied in Dozier and Silverstein [On the empirical distribution of eigenvalues of large dimensional information-plus-noise type matrices, 2004, submitted for publication], is presented. It is shown that, away from zero, the limiting distribution possesses a continuous density. The density is analytic where it is positive and, for the most relevant cases of a in the boundary of its support, exhibits behavior closely resembling that of |x-a| for x near a. A procedure to determine its support is also analyzed.