treemisc: Data Sets and Functions to Accompany "Tree-Based Methods for Statistical Learning in R"

Miscellaneous data sets and functions to accompany Greenwell (2022) "Tree-Based Methods for Statistical Learning in R" <doi:10.1201/9781003089032>.

Version: 0.0.1
Depends: R (≥ 4.0.0)
Imports: Matrix, Rcpp (≥ 1.0.1), rpart, stats, utils
LinkingTo: Rcpp
Suggests: AmesHousing, gbm, glmnet (≥ 3.0), graphics, mlbench, party, partykit, randomForest, ranger, rpart.plot, tinytest
Published: 2022-10-19
Author: Brandon M. Greenwell ORCID iD [aut, cre]
Maintainer: Brandon M. Greenwell <greenwell.brandon at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README
CRAN checks: treemisc results

Documentation:

Reference manual: treemisc.pdf

Downloads:

Package source: treemisc_0.0.1.tar.gz
Windows binaries: r-devel: treemisc_0.0.1.zip, r-release: treemisc_0.0.1.zip, r-oldrel: treemisc_0.0.1.zip
macOS binaries: r-release (arm64): treemisc_0.0.1.tgz, r-oldrel (arm64): treemisc_0.0.1.tgz, r-release (x86_64): treemisc_0.0.1.tgz

Linking:

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