Man pages for ecpc
Flexible Co-Data Learning for High-Dimensional Prediction
| coef.ecpc | Obtain coefficients from 'ecpc' object |
| createCon | Create a list of constraints for co-data weight estimation |
| createGroupset | Create a group set (groups) of variables |
| createS | Create a generalised penalty matrix |
| createZforGroupset | Create a co-data matrix Z for a group set |
| createZforSplines | Create a co-data matrix Z of splines |
| cv.ecpc | Cross-validation for 'ecpc' |
| ecpc | Fit adaptive multi-group ridge GLM with hypershrinkage |
| ecpc-package | Flexible Co-Data Learning for High-Dimensional Prediction |
| hierarchicalLasso | Fit hierarchical lasso using LOG penalty |
| obtainHierarchy | Obtain hierarchy |
| plot.ecpc | Plot an 'ecpc' object |
| postSelect | Perform posterior selection |
| predict.ecpc | Predict for new samples for 'ecpc' object |
| print.ecpc | Print summary of 'ecpc' object |
| produceFolds | Produce folds |
| simDat | Simulate data |
| splitMedian | Discretise continuous data in multiple granularities |
| visualiseGroupset | Visualise a group set |
| visualiseGroupsetweights | Visualise estimated group set weights |
| visualiseGroupweights | Visualise estimated group weights |
