Entrywise limit theorems for eigenvectors of signal-plus-noise matrix models with weak signals
Author:
Affiliation:
1. Department of Statistics, Indiana University, Bloomington, United States
Publisher
Bernoulli Society for Mathematical Statistics and Probability
Subject
Statistics and Probability
Reference85 articles.
1. Vershynin, R. (2012). Introduction to the non-asymptotic analysis of random matrices. In Compressed Sensing 210–268. Cambridge: Cambridge Univ. Press.
2. van der Vaart, A.W. (1998). Asymptotic Statistics. Cambridge Series in Statistical and Probabilistic Mathematics 3. Cambridge: Cambridge Univ. Press. 10.1017/CBO9780511802256
3. Bai, Z. and Silverstein, J.W. (2010). Spectral Analysis of Large Dimensional Random Matrices, 2nd ed. Springer Series in Statistics. New York: Springer. 10.1007/978-1-4419-0661-8
4. Airoldi, E.M., Blei, D.M., Fienberg, S.E. and Xing, E.P. (2008). Mixed membership stochastic blockmodels. J. Mach. Learn. Res. 9 1981–2014.
5. Anderson, T.W. (2003). An Introduction to Multivariate Statistical Analysis, 3rd ed. Wiley Series in Probability and Statistics. Hoboken, NJ: Wiley Interscience.
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1. Entrywise limit theorems for eigenvectors of signal-plus-noise matrix models with weak signals;Bernoulli;2024-02-01
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