R: Exploring Friedman's Boosting Algorithm for Regularized Linear Regression

# Exploring Friedman's Boosting Algorithm for Regularized Linear Regression

## Documentation for package ‘l2boost’ version 1.0.3

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

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. 'coef' is a generic function which extracts model coefficients from objects returned by modeling functions.
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.
error.bars | nice standard errors for plots
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.
plot.lines | plots.lines is used by 'plot.l2boost' to the path lines (each j, against each r-step)
predict.l2boost | predict method for l2boost models.
print.l2boost | print method for 'l2boost' and 'cv.l2boost' objects.
print.summary.l2boost | Unimplemented generic function These are placeholders right now.
residuals.l2boost | Model residuals for the training set of an l2boost model object
summary.l2boost | Unimplemented generic function These are placeholders right now.
VAR | This is a hidden function of the l2boost package. VAR is a helper function that specifically returns NA if all values of the argument x are NA, otherwise, it returns a var object.