Man pages for multiridge
Fast Cross-Validation for Multi-Penalty Ridge Regression
| augment | Augment data with zeros. |
| betasout | Coefficient estimates from (converged) IWLS fit |
| createXblocks | Create list of paired data blocks |
| createXXblocks | Creates list of (unscaled) sample covariance matrices |
| CVfolds | Creates (repeated) cross-validation folds |
| CVscore | Cross-validated score |
| dataXXmirmeth | Contains R-object 'dataXXmirmeth' |
| doubleCV | Double cross-validation for estimating performance of... |
| fastCV2 | Fast cross-validation per data block |
| IWLSCoxridge | Iterative weighted least squares algorithm for Cox ridge... |
| IWLSridge | Iterative weighted least squares algorithm for linear and... |
| mgcv_lambda | Maximum marginal likelihood score |
| mlikCV | Outer-loop cross-validation for estimating performance of... |
| multiridge-package | Fast cross-validation for multi-penalty ridge regression |
| optLambdas | Find optimal ridge penalties. |
| optLambdas_mgcv | Find optimal ridge penalties with maximimum marginal... |
| optLambdas_mgcvWrap | Find optimal ridge penalties with sequential optimization. |
| optLambdasWrap | Find optimal ridge penalties with sequential optimization. |
| predictIWLS | Predictions from ridge fits |
| Scoring | Evaluate predictions |
| setupParallel | Setting up parallel computing |
| SigmaFromBlocks | Create penalized sample cross-product matrix |
