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CRAN: Package radiant.model

radiant.model: Model Menu for Radiant: Business Analytics using R and Shiny

The Radiant Model menu includes interfaces for linear and logistic regression, naive Bayes, neural networks, classification and regression trees, model evaluation, collaborative filtering, decision analysis, and simulation. The application extends the functionality in 'radiant.data'.

Version: 1.6.9
Depends: R (≥ 4.3.0), radiant.data (≥ 1.6.6)
Imports: radiant.basics (≥ 1.6.6), shiny (≥ 1.8.1), nnet (≥ 7.3.12), NeuralNetTools (≥ 1.5.1), sandwich (≥ 2.3.4), car (≥ 2.1.3), ggplot2 (≥ 3.4.2), scales (≥ 1.2.1), data.tree (≥ 0.7.4), stringr (≥ 1.1.0), lubridate (≥ 1.7.2), tidyr (≥ 0.8.2), dplyr (≥ 1.1.2), tidyselect (≥ 1.2.0), rlang (≥ 0.4.10), magrittr (≥ 1.5), DiagrammeR (≥ 1.0.9), import (≥ 1.1.0), psych (≥ 1.8.4), e1071 (≥ 1.6.8), rpart (≥ 4.1.11), ggrepel (≥ 0.8), broom (≥ 0.7.0), patchwork (≥ 1.0.0), ranger (≥ 0.11.2), xgboost (≥ 1.6.0.1), vip (≥ 0.3.2), stringi, yaml
Suggests: pdp (≥ 0.8.1), testthat (≥ 2.0.0), pkgdown (≥ 1.1.0)
Published: 2026-01-10
DOI: 10.32614/CRAN.package.radiant.model
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant at rady.ucsd.edu>
BugReports: https://github.com/radiant-rstats/radiant.model/issues/
License: AGPL-3 | file LICENSE
URL: https://github.com/radiant-rstats/radiant.model/, https://radiant-rstats.github.io/radiant.model/, https://radiant-rstats.github.io/docs/
NeedsCompilation: no
Language: en-US
Materials: README, NEWS
CRAN checks: radiant.model results

Documentation:

Reference manual: radiant.model.html , radiant.model.pdf

Downloads:

Package source: radiant.model_1.6.9.tar.gz
Windows binaries: r-devel: radiant.model_1.6.9.zip, r-release: radiant.model_1.6.9.zip, r-oldrel: radiant.model_1.6.9.zip
macOS binaries: r-release (arm64): radiant.model_1.6.9.tgz, r-oldrel (arm64): radiant.model_1.6.9.tgz, r-release (x86_64): radiant.model_1.6.9.tgz, r-oldrel (x86_64): radiant.model_1.6.9.tgz
Old sources: radiant.model archive

Reverse dependencies:

Reverse depends: radiant
Reverse imports: radiant.multivariate

Linking:

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