Regression shrinkage and selection via least quantile shrinkage and selection operator.
Over recent years, the state-of-the-art lasso and adaptive lasso have aquired remarkable consideration. Unlike the lasso technique, adaptive lasso welcomes the variables' effects in penalty meanwhile specifying adaptive weights to penalize coefficients in a different manner. However, if the ini...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2023-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0266267 |