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RBF (version 2.1.1)

Robust Backfitting

Description

A robust backfitting algorithm for additive models based on (robust) local polynomial kernel smoothers. It includes both bounded and re-descending (kernel) M-estimators, and it computes predictions for points outside the training set if desired. See Boente, Martinez and Salibian-Barrera (2017) and Martinez and Salibian-Barrera (2021) for details.

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Version

Install

install.packages('RBF')

Monthly Downloads

164

Version

2.1.1

License

GPL (>= 3.0)

Maintainer

Matias Salibian-Barrera

Last Published

August 31st, 2023

Functions in RBF (2.1.1)

backf.rob

Robust Backfitting
predict.backf

Fitted values for objects of class backf.
print.backf

Print a Marginal Integration procedure
RBF-package

A robust backfitting algorithm for additive models.
backf.cl

Classic Backfitting
k.epan

Epanechnikov kernel
plot.backf

Diagnostic plots for objects of class backf
summary.backf

Summary for additive models fits using backfitting
residuals.backf

Residuals for objects of class backf
formula.backf

Additive model formula
fitted.values.backf

Fitted values for objects of class backf
deviance.backf

Deviance for objects of class backf
psi.tukey

Derivative of Tukey's bi-square loss function.
psi.huber

Derivative of Huber's loss function.