Marginal false discovery rate approaches to inference on penalized regression models
Data containing large number of variables is becoming increasingly more common and sparsity inducing penalized regression methods, such the lasso, have become a popular analysis tool for these datasets due to their ability to naturally perform variable selection. However, quantifying the importance...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | English |
| Published: |
University of Iowa
2018
|
| Subjects: | |
| Online Access: | https://ir.uiowa.edu/etd/6474 https://ir.uiowa.edu/cgi/viewcontent.cgi?article=7974&context=etd |