Large sample correlation matrices: a comparison theorem and its applications (Q2082651)

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English	Large sample correlation matrices: a comparison theorem and its applications	scientific article

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instance of

scholarly article

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title

Large sample correlation matrices: a comparison theorem and its applications (English)

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author

Johannes Heiny

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published in

Electronic Journal of Probability

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publication date

4 October 2022

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full work available at URL

https://arxiv.org/abs/2201.00916

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https://projecteuclid.org/journals/electronic-journal-of-probability/volume-27/issue-none/Large-sample-correlation-matrices-a-comparison-theorem-and-its/10.1214/22-EJP817.full

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zbMATH Keywords

largest eigenvalue

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limiting spectral distribution

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sample correlation matrix

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smallest eigenvalue

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population covariance matrix

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MaRDI profile type

MaRDI publication profile

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cites work

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On sample eigenvalues in a generalized spiked population model

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Largest entries of sample correlation matrices from equi-correlated normal populations

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On the distribution of the largest eigenvalue in principal components analysis

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Spectrum estimation from samples

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Robustness of the sample correlation -- the bivariate lognormal case

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Some strong limit theorems for the largest entries of sample correlation matrices

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On the limit of the largest eigenvalue of the large dimensional sample covariance matrix

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Identifiers

zbMATH Open document ID

1498.60033

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DOI

10.1214/22-EJP817

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:2082651