Dimension reduction methods with applications to high dimensional data with a censored response
Dimension reduction methods have come to the forefront of many applications where the number of covariates, p, far exceed the sample size, N. For example, in survival analysis studies using microarray gene expression data, 10--30K expressions per patient are collected, but only a few hundred patient...
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| Format: | Others |
| Language: | English |
| Published: |
2011
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| Online Access: | http://hdl.handle.net/1911/61967 |