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Implements a family of robust tree-based boosting methods for functional regression, including procedures based on least absolute deviation, M-estimation, and MM-estimation. The package also includes a non-robust tree-based boosting method introduced in Ju X and Salibian-Barrera M. (2024) <doi:10.1007/s00180-023-01364-2>. Functions are provided for model fitting and prediction in regression settings with functional predictors.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | stats, rpart, lme4, splines, RobStatTM |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2026-10-16 |
| DOI: | 10.32614/CRAN.package.RTFBoost |
| Author: | Xiaomeng Ju [aut, cre], Matias Salibian-Barrera [aut] |
| Maintainer: | Xiaomeng Ju <xiaomengju at uvic.ca> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | RTFBoost results |
| Reference manual: | RTFBoost.html , RTFBoost.pdf |
| Package source: | RTFBoost_0.1.0.tar.gz |
| Windows binaries: | r-devel: RTFBoost_0.1.0.zip, r-release: RTFBoost_0.1.0.zip, r-oldrel: RTFBoost_0.1.0.zip |
| macOS binaries: | r-release (arm64): RTFBoost_0.1.0.tgz, r-oldrel (arm64): RTFBoost_0.1.0.tgz, r-release (x86_64): RTFBoost_0.1.0.tgz, r-oldrel (x86_64): RTFBoost_0.1.0.tgz |
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