Asymptotics of the leading sample eigenvalues for a spiked covariance model

By D. Paul. 2004

51 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/df473316b459666f303aa2f384b1d01f9d74b217

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Debashis Paul
2. Jianfeng Yao
3. Tommaso Cai
4. Z. Bai
5. A. Onatski
6. Z. Bao
7. Terence Tao
8. Boaz Nadler

Citations in the corpus

• The Distributions of Random Matrix Theory and their Applications (2009, background): “For real Wishart matrices, Paul [25] shows that if π1 > wc is simple, then l̂1 exhibits Gaussian fluctuations.”
• ASYMPTOTICS OF SAMPLE EIGENSTRUCTURE FOR A LARGE DIMENSIONAL SPIKED COVARIANCE MODEL (2007, background): “The proof can be found in Paul (2004).”
• Covariance regularization by thresholding (2009, unknown): “30 79 v1 [ m at h. ST ] 2 0 Ja n 20 09 The Annals of Statistics 2008, Vol. 36, No. 6, 2577–2604 DOI: 10.1214/08-AOS600 c© Institute of Mathematical Statistics, 2008”
• Finite sample approximation results for principal component analysis: a matrix perturbation approach (2009, methodology): “A similar approach was recently independently derived by Paul [32].”
• Statistical Significance of Clustering for High-Dimension, Low–Sample Size Data (2008, unknown): “Similar results were obtained by Paul (2007).”
• The Largest Eigenvalue of Rank One Deformation of Large Wigner Matrices (2006, background): “Nevertheless, it can be inferred from the results of [8] and communications with J.”
• Regularized estimation of large covariance matrices (2008, unknown): “19 09 v1 [ m at h. ST ] 1 3 M ar 2 00 8 The Annals of Statistics 2008, Vol. 36, No. 1, 199–227 DOI: 10.1214/009053607000000758 c© Institute of Mathematical Statistics, 2008”
• Central limit theorems for eigenvalues in a spiked population model (2008, background): “In this perspective, assuming that the population vector is real Gaussian with a diagonal covariance matrix and that the M spike eigenvalues are all simple, [12] found that each of the M largest sample eigenvalues has a Gaussian limiting distribution.”
• Weak and Strong Cross Section Dependence and Estimation of Large Panels (2011, unknown): “Similar panel data models have been analyzed by Pesaran (2006), Kapetanios, Pesaran, and Yagamata (2009), and Pesaran and Tosetti (2009). Pesaran (2006) introduced CCE estimators in a panel model where m1 is …xed and m2 = 0, and ift represents a strong factor structure.”
• Large Panels with Common Factors and Spatial Correlation (2011, background): “See, for example, Onatski (2009), and Paul (2007).”