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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> for details.

copied from cf-post-staging / r-rbf
Type Size Name Uploaded Downloads Labels
conda 104.7 kB | win-64/r-rbf-2.0.1-r40hda5aaf8_0.tar.bz2  5 years and 1 day ago 984 main
conda 105.1 kB | win-64/r-rbf-2.0.1-r36hda5aaf8_0.tar.bz2  5 years and 1 day ago 994 main
conda 100.1 kB | osx-64/r-rbf-2.0.1-r40h800e0f2_0.tar.bz2  5 years and 1 day ago 306 main
conda 100.4 kB | osx-64/r-rbf-2.0.1-r36h800e0f2_0.tar.bz2  5 years and 1 day ago 306 main
conda 96.5 kB | linux-64/r-rbf-2.0.1-r40hcdcec82_0.tar.bz2  5 years and 1 day ago 3148 main
conda 96.8 kB | linux-64/r-rbf-2.0.1-r36hcdcec82_0.tar.bz2  5 years and 1 day ago 3156 main

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