Man pages for quadrupen
Sparse and Group Sparse Linear Models
| bounded_reg | Fit a linear model with infinity-norm plus ridge-like... |
| BoundedRegressionFit | Class "BoundedRegression" |
| coef.QuadrupenFit | Extract model coefficients |
| criteria | Penalized criteria based on estimation of degrees of freedom |
| cross_validate | Cross-validation for Quadrupen object |
| CrossValidation | Class CrossValidation |
| DataModel | Data Class |
| deviance.QuadrupenFit | Extract model deviance |
| fitted.QuadrupenFit | Extracts model fitted values |
| fused_lasso | A function for fitting generalized fused-Lasso problems |
| FusedLassoFit | Class "FusedLassoFit" |
| group_lava | Fit a linear model with group-lava regularization |
| GroupLavaFit | Class "GroupLavaFit" |
| group_sparse_lm | Fit a linear model with (sparse) group regularisation |
| InformationCriteria | Class InformationCriteria |
| isQuadrupenFit | Auxiliary functions to check the given class of an object |
| lava | Fit a linear model with lava regularization |
| LavaFit | Class "LavaFit" |
| plot.QuadrupenFit | Plot method for quadrupen objects |
| predict.QuadrupenFit | Perform model prediction |
| QuadrupenFit | Class "QuadrupenFit" |
| quadrupen-package | Sparsity by Worst-Case Quadratic Penalties |
| residuals.QuadrupenFit | Extract model residuals |
| ridge | Fit a linear model with a structured ridge regularization |
| RidgeRegressionFit | Class "RidgeRegressionFit" |
| selection | Variable selection from a stability path |
| SparseFit | Class "SparseFit" |
| SparseGroupFit | Class "SparseGroupFit" |
| sparse_lm | Fit a linear model with sparse regularization |
| stability | Stability selection for Quadrupen object |
| StabilityPath | Class StabilityPath |
