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PCA in High Dimensions: An orientation
When the data are high dimensional, widely used multivariate statistical methods such as principal component analysis can behave in unexpected ways. In settings where the dimension of the observations is comparable to the sample size, upward bias in sample eigenvalues and inconsistency of sample eig...
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| Publicado no: | Proc IEEE Inst Electr Electron Eng |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6167023/ https://ncbi.nlm.nih.gov/pubmed/30287970 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/JPROC.2018.2846730 |
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