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https://projecteuclid.org/euclid.aop/1022855421
Ann. Probab. Volume 26, Number 1 (1998), 316-345. No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.149.6715&rep=rep1&type=pdf
conditions on the eigenvalues of An and Bn, with probability 1, there will be no eigenvalues in any closed interval outside the support of the limiting distribution, for su–ciently large n. The problem is motivated by applications in spatio-temporal statistics and wireless communications.
https://www.worldscientific.com/doi/10.1142/S2010326311500043
In this paper we show that, under certain conditions on R n, for any closed interval in ℝ + outside the support of the limiting distribution, then, almost surely, no eigenvalues of …Cited by: 25
https://jack.math.ncsu.edu/noeigenvalues.pdf
No Eigenvalues Outside the Support of the Limiting Spectral Distribution of Information-Plus-Noise Type Matrices Zhidong Baiy1 and Jack W. Silversteinz2 yKLAS MOE & School of Mathematics and Statistics, Northeast Normal University,
https://www.sciencedirect.com/science/article/pii/S0047259X08001024
We show that, under appropriate conditions on the eigenvalues of A n and B n, with probability 1, there will be no eigenvalues in any closed interval outside the support of the limiting distribution, for sufficiently large n. The problem is motivated by applications in spatio-temporal statistics and …Cited by: 74
https://repository.kaust.edu.sa/bitstream/handle/10754/610651/07464912.pdf?sequence=1&isAllowed=y
eigenvalues of 1 n n in any closed interval outside the support of the limiting distribution. This result, often referred to as a no-eigenvalue result, has been established in [8] for the simple-correlated case where the columns of nare correlated with the same correlation matrix and in [1] for non-centered uncorrelated models.
https://arxiv.org/pdf/1801.03319
/No eigenvalues outside the support 3 are equal to 1, apparently, the spectrum of S n is no longer a good estimator of Σ p.A consequent question one may ask is: what if there is no exact structure on YCited by: 1
https://jack.math.ncsu.edu/noeigenvalues.pdf
the eigenvalues of C nconverges a.s. to a nonrandom limit. In this paper we show that, under certain conditions on R n, for any closed interval in R+ outside the support of the limiting distribution, then, almost surely, no eigenvalues of C nwill appear in this interval for all nlarge.
https://repository.kaust.edu.sa/bitstream/handle/10754/610651/07464912.pdf?sequence=1&isAllowed=y
eigenvalues of 1 n n in any closed interval outside the support of the limiting distribution. This result, often referred to as a no-eigenvalue result, has been established in [8] for the simple-correlated case where the columns of nare correlated with the same correlation matrix and in [1] for non-centered uncorrelated models.
https://www.sciencedirect.com/science/article/pii/S0047259X08001024
We show that, under appropriate conditions on the eigenvalues of A n and B n, with probability 1, there will be no eigenvalues in any closed interval outside the support of the limiting distribution, for sufficiently large n. The problem is motivated by applications in spatio-temporal statistics and …Cited by: 77
https://www.semanticscholar.org/paper/No-eigenvalues-outside-the-support-of-the-limiting-Bai-Silverstein/dcfddb33ea6fa0dba831b2a51e87a64b7021a167
No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices @inproceedings{Bai1998NoEO, title={No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices}, author={Z. D. Bai and Jack W. Silverstein}, year={1998} }
https://repository.kaust.edu.sa/handle/10754/610651
Following the approach proposed in [1], we prove that under some mild conditions, there is no eigenvalue outside the limiting support of generally correlated Gaussian matrices. As an outcome of this result, we establish that the smallest singular value …Cited by: 7
https://projecteuclid.org/euclid.aop/1022855421
Ann. Probab. Volume 26, Number 1 (1998), 316-345. No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices
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