Fits a multivariate model of decision trees for multiple, continuous outcome variables. A model for each outcome variable is fit separately, selecting predictors that explain covariance in the outcomes. Built on top of 'gbm', which fits an ensemble of decision trees to univariate outcomes.

Maintainer: Patrick Miller <patrick.mil10 at gmail.com>

Author(s): Patrick Miller*

Install package and any missing dependencies by running this line in your R console:

install.packages("mvtboost")

Depends R (>= 3.0.0)
Imports gbm, RColorBrewer, stats, graphics, grDevices, utils,
Suggests testthat, plyr, MASS, parallel, lars, ggplot2, knitr, rmarkdown
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Package mvtboost
Materials
URL https://github.com/patr1ckm/mvtboost
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Version 0.5.0
Published 2016-12-05
License GPL (>= 2) | file LICENSE
BugReports https://github.com/patr1ckm/mvtboost/issues
SystemRequirements
NeedsCompilation no
Citation
CRAN checks mvtboost check results
Package source mvtboost_0.5.0.tar.gz