ecpc-package | 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 |
hierarchicalLasso | Fit hierarchical lasso using LOG penalty |
obtainHierarchy | Obtain hierarchy |
penalties | Obtain coefficients from 'ecpc' object |
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 |
summary.ecpc | Print summary of 'ecpc' object |
visualiseGroupset | Visualise a group set |
visualiseGroupsetweights | Visualise estimated group set weights |
visualiseGroupweights | Visualise estimated group weights |