| l2boost-package | Efficient implementation of Friedman's boosting algorithm for linear regression using an l2-loss function and coordinate direction (design matrix columns) basis functions. |
| coef.l2boost | Extract model coefficients from an l2boost model object at any point along the solution path indexed by step m. |
| cv.l2boost | K-fold cross-validation using 'l2boost'. |
| diabetes | Blood and other measurements in diabetics [Hastie and Efron (2012)] |
| elasticNetSim | A blocked correlated data simulation. |
| fitted.l2boost | Extract the fitted model estimates along the solution path for an l2boost model. |
| l2boost | Generic gradient descent boosting method for linear regression. |
| l2boost.default | Generic gradient descent boosting method for linear regression. |
| l2boost.formula | Generic gradient descent boosting method for linear regression. |
| mvnorm.l2boost | multivariate normal data simulations. |
| plot.l2boost | Plotting for 'l2boost' objects. |
| predict.l2boost | predict method for l2boost models. |
| print.l2boost | print method for 'l2boost' and 'cv.l2boost' objects. |
| residuals.l2boost | Model residuals for the training set of an l2boost model object |