Package: RBF 2.1.1
RBF: Robust Backfitting
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) <doi:10.1080/10485252.2017.1369077> and Martinez and Salibian-Barrera (2021) <doi:10.21105/joss.02992> for details.
Authors:
RBF_2.1.1.tar.gz
RBF_2.1.1.zip(r-4.5)RBF_2.1.1.zip(r-4.4)RBF_2.1.1.zip(r-4.3)
RBF_2.1.1.tgz(r-4.4-x86_64)RBF_2.1.1.tgz(r-4.4-arm64)RBF_2.1.1.tgz(r-4.3-x86_64)RBF_2.1.1.tgz(r-4.3-arm64)
RBF_2.1.1.tar.gz(r-4.5-noble)RBF_2.1.1.tar.gz(r-4.4-noble)
RBF_2.1.1.tgz(r-4.4-emscripten)RBF_2.1.1.tgz(r-4.3-emscripten)
RBF.pdf |RBF.html✨
RBF/json (API)
NEWS
# Install 'RBF' in R: |
install.packages('RBF', repos = c('https://msalibian.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/msalibian/rbf/issues
Last updated 1 years agofrom:3b0d553995. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 06 2024 |
R-4.5-win-x86_64 | OK | Nov 06 2024 |
R-4.5-linux-x86_64 | OK | Nov 06 2024 |
R-4.4-win-x86_64 | OK | Nov 06 2024 |
R-4.4-mac-x86_64 | OK | Nov 06 2024 |
R-4.4-mac-aarch64 | OK | Nov 06 2024 |
R-4.3-win-x86_64 | OK | Nov 06 2024 |
R-4.3-mac-x86_64 | OK | Nov 06 2024 |
R-4.3-mac-aarch64 | OK | Nov 06 2024 |
Exports:backf.clbackf.robk.epanpsi.huberpsi.tukey
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
A robust backfitting algorithm for additive models. | RBF-package RBF |
Classic Backfitting | backf.cl |
Robust Backfitting | backf.rob |
Deviance for objects of class 'backf' | deviance.backf |
Fitted values for objects of class 'backf' | fitted.values.backf |
Additive model formula | formula.backf |
Epanechnikov kernel | k.epan |
Diagnostic plots for objects of class 'backf' | plot.backf |
Fitted values for objects of class 'backf'. | predict.backf |
Print a Marginal Integration procedure | print.backf |
Derivative of Huber's loss function. | psi.huber |
Derivative of Tukey's bi-square loss function. | psi.tukey |
Residuals for objects of class 'backf' | residuals.backf |
Summary for additive models fits using backfitting | summary.backf summary.backf.cl summary.backf.rob |