Package: l2boost 1.0.3

l2boost: Exploring Friedman's Boosting Algorithm for Regularized Linear Regression

Efficient implementation of Friedman's boosting algorithm with l2-loss function and coordinate direction (design matrix columns) basis functions.

Authors:John Ehrlinger [aut, cre], Hemant Ishwaran [aut]

l2boost_1.0.3.tar.gz
l2boost_1.0.3.zip(r-4.5)l2boost_1.0.3.zip(r-4.4)l2boost_1.0.3.zip(r-4.3)
l2boost_1.0.3.tgz(r-4.4-any)l2boost_1.0.3.tgz(r-4.3-any)
l2boost_1.0.3.tar.gz(r-4.5-noble)l2boost_1.0.3.tar.gz(r-4.4-noble)
l2boost_1.0.3.tgz(r-4.4-emscripten)l2boost_1.0.3.tgz(r-4.3-emscripten)
l2boost.pdf |l2boost.html
l2boost/json (API)
NEWS

# Install 'l2boost' in R:
install.packages('l2boost', repos = c('https://ehrlinger.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ehrlinger/l2boost/issues

Datasets:
  • diabetes - Blood and other measurements in diabetics [Hastie and Efron (2012)]

On CRAN:

3.48 score 6 stars 10 scripts 177 downloads 4 exports 1 dependencies

Last updated 3 years agofrom:b924457c5f. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 11 2024
R-4.5-winNOTEOct 11 2024
R-4.5-linuxNOTEOct 11 2024
R-4.4-winNOTEOct 11 2024
R-4.4-macNOTEOct 11 2024
R-4.3-winNOTEOct 11 2024
R-4.3-macNOTEOct 11 2024

Exports:cv.l2boostelasticNetSiml2boostmvnorm.l2boost

Dependencies:MASS

Readme and manuals

Help Manual

Help pageTopics
Efficient implementation of Friedman's boosting algorithm for linear regression using an l2-loss function and coordinate direction (design matrix columns) basis functions.l2boost-package
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.coef.l2boost
K-fold cross-validation using 'l2boost'.cv.l2boost
Blood and other measurements in diabetics [Hastie and Efron (2012)]diabetes
A blocked correlated data simulation.elasticNetSim
nice standard errors for plotserror.bars
Extract the fitted model estimates along the solution path for an l2boost model.fitted.l2boost
Generic gradient descent boosting method for linear regression.l2boost l2boost.default l2boost.formula
multivariate normal data simulations.mvnorm.l2boost
Plotting for 'l2boost' objects.plot.l2boost
plots.lines is used by 'plot.l2boost' to the path lines (each j, against each r-step)plot.lines
predict method for l2boost models.predict.l2boost
print method for 'l2boost' and 'cv.l2boost' objects.print.l2boost
Unimplemented generic function These are placeholders right now.print.summary.l2boost
Model residuals for the training set of an l2boost model objectresiduals.l2boost
Unimplemented generic function These are placeholders right now.summary.l2boost
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.VAR