ON DETERMINING THE NUMBER OF SPIKES IN A HIGH-DIMENSIONAL SPIKED POPULATION MODEL

DOI10.1142/S201032631150002XzbMath1244.62028arXiv1104.2677MaRDI QIDQ2893152

Damien Passemier, Jian-feng Yao

Publication date: 26 June 2012

Published in: Random Matrices: Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1104.2677

zbMATH Keywords

extreme eigenvaluesfactor modelhigh-dimensional statisticstracy-widom lawssample covariance matrices

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Random matrices (probabilistic aspects) (60B20) Eigenvalues, singular values, and eigenvectors (15A18)

Related Items (16)

Variance variation criterion and consistency in estimating the number of significant signals of high-dimensional PCA ⋮ Optimal prediction in the linearly transformed spiked model ⋮ Order Determination for Spiked Type Models ⋮ A Universal Test on Spikes in a High-Dimensional Generalized Spiked Model and Its Applications ⋮ Order determination for spiked-type models with a divergent number of spikes ⋮ Estimation of the number of spikes, possibly equal, in the high-dimensional case ⋮ Generalized four moment theorem and an application to CLT for spiked eigenvalues of high-dimensional covariance matrices ⋮ Canonical correlation coefficients of high-dimensional Gaussian vectors: finite rank case ⋮ Rapid evaluation of the spectral signal detection threshold and Stieltjes transform ⋮ Matrix Denoising for Weighted Loss Functions and Heterogeneous Signals ⋮ A note on the CLT of the LSS for sample covariance matrix from a spiked population model ⋮ Likelihood ratio test for partial sphericity in high and ultra-high dimensions ⋮ Unnamed Item ⋮ Spiked sample covariance matrices with possibly multiple bulk components ⋮ Hypergeometric functions of matrix arguments and linear statistics of multi-spiked Hermitian matrix models ⋮ On generalized expectation-based estimation of a population spectral distribution from high-dimensional data

Cites Work

• Central limit theorems for eigenvalues in a spiked population model
• On the distribution of the largest eigenvalue in principal components analysis
• Eigenvalues of large sample covariance matrices of spiked population models

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