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 |