Generalized LassO applied to knot selection in multivariate B-splinE Regression (GLOBER) implements a novel approach for estimating functions in a multivariate nonparametric regression model based on an adaptive knot selection for B-splines using the Generalized Lasso. For further details we refer the reader to the paper Savino, M. E. and Lévy-Leduc, C. (2023), <doi:10.48550/arXiv.2306.00686>.
| Version: | 1.0 |
| Depends: | R (≥ 3.5.0), Matrix, genlasso, fda, parallel |
| Imports: | ggplot2, plot3D |
| Suggests: | knitr, markdown |
| Published: | 2023-06-07 |
| DOI: | 10.32614/CRAN.package.glober |
| Author: | M. E. Savino |
| Maintainer: | Mary E. Savino <mary.savino at outlook.fr> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | glober results |
| Reference manual: | glober.html , glober.pdf |
| Vignettes: |
glober package (source, R code) |
| Package source: | glober_1.0.tar.gz |
| Windows binaries: | r-devel: glober_1.0.zip, r-release: glober_1.0.zip, r-oldrel: glober_1.0.zip |
| macOS binaries: | r-release (arm64): glober_1.0.tgz, r-oldrel (arm64): glober_1.0.tgz, r-release (x86_64): glober_1.0.tgz, r-oldrel (x86_64): glober_1.0.tgz |
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