Optimality and sub-optimality of PCA I: Spiked random matrix models
A central problem of random matrix theory is to understand the eigenvalues of spiked random matrix models, introduced by Johnstone, in which a prominent eigenvector (or “spike”) is planted into a random matrix. These distributions form natural statistical models for principal component analysis (PCA...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Institute of Mathematical Statistics
2020
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| Online Access: | https://hdl.handle.net/1721.1/125398 |