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Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.

copied from cf-post-staging / r-mboost
Type Size Name Uploaded Downloads Labels
conda 2.6 MB | win-64/r-mboost-2.9_9-r41h6d2157b_0.conda  2 years and 5 months ago 560 main
conda 2.6 MB | osx-64/r-mboost-2.9_9-r43hb2c329c_0.conda  2 years and 5 months ago 452 main
conda 2.6 MB | osx-64/r-mboost-2.9_9-r42hb2c329c_0.conda  2 years and 5 months ago 506 main
conda 2.6 MB | linux-64/r-mboost-2.9_9-r43h57805ef_0.conda  2 years and 5 months ago 2432 main
conda 2.6 MB | linux-64/r-mboost-2.9_9-r42h57805ef_0.conda  2 years and 5 months ago 2404 main

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