PCA Consistency for Non-Gaussian Data in High Dimension, Low Sample Size Context
Author:
Publisher
Informa UK Limited
Subject
Statistics and Probability
Link
http://www.tandfonline.com/doi/pdf/10.1080/03610910902936083
Reference9 articles.
1. The high-dimension, low-sample-size geometric representation holds under mild conditions
2. Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices
3. Eigenvalues of large sample covariance matrices of spiked population models
4. Geometric representation of high dimension, low sample size data
5. On the distribution of the largest eigenvalue in principal components analysis
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