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-4.7)RBF_2.1.1.zip(r-4.6)RBF_2.1.1.zip(r-4.5)
RBF_2.1.1.tgz(r-4.6-x86_64)RBF_2.1.1.tgz(r-4.6-arm64)RBF_2.1.1.tgz(r-4.5-x86_64)RBF_2.1.1.tgz(r-4.5-arm64)
RBF_2.1.1.tar.gz(r-4.7-arm64)RBF_2.1.1.tar.gz(r-4.7-x86_64)RBF_2.1.1.tar.gz(r-4.6-arm64)RBF_2.1.1.tar.gz(r-4.6-x86_64)
RBF_2.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RBF/json (API)
| # 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 from:3b0d553995. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 122 | ||
| linux-devel-x86_64 | OK | 122 | ||
| source / vignettes | OK | 249 | ||
| linux-release-arm64 | OK | 121 | ||
| linux-release-x86_64 | OK | 121 | ||
| macos-release-arm64 | OK | 119 | ||
| macos-release-x86_64 | OK | 157 | ||
| macos-oldrel-arm64 | OK | 87 | ||
| macos-oldrel-x86_64 | OK | 172 | ||
| windows-devel | OK | 78 | ||
| windows-release | OK | 80 | ||
| windows-oldrel | OK | 92 | ||
| wasm-release | OK | 100 |
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 |
