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 that explain covariance in multiple outcomes.
Package is built on top of 'gbm'.
testthat, plyr, MASS, parallel, lars, ggplot2, knitr,
rmarkdown
gbm, RColorBrewer, stats, graphics, grDevices, utils,

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 that explain covariance in
multiple outcomes. Package is built on top of 'gbm', which fits an ensemble
of decision trees to univariate outcomes.

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.

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.

This package contains functions to run fixed effects or
random effects multivariate meta-analysis.

Functions to run fixed effects or random effects multivariate meta-analysis.

Alan Genz <AlanGenz@wsu.edu>,
Frank Bretz <bretz@ifgb.uni-hannover.de>,
R port by Torsten Hothorn <Torsten.Hothorn@rzmail.uni-erlangen.de>
computes the multivariate normal and t distribution

Alan Genz <AlanGenz@wsu.edu>,
Frank Bretz <frank.bretz@pharma.novartis.com>,
R port by Torsten Hothorn <Torsten.Hothorn@rzmail.uni-erlangen.de>

Alan Genz <AlanGenz@wsu.edu>,
Frank Bretz <frank.bretz@pharma.novartis.com>,
R port by Torsten Hothorn <Torsten.Hothorn@R-project.org>
Computes multivariate normal and t probabilities, quantiles and
densities.

Alan Genz, Frank Bretz and Torsten Hothorn
with contributions by Tetsuhisa Miwa, Xuefei Mi, Friedrich Leisch
and Fabian Scheipl
Computes multivariate normal and t probabilities, quantiles,
random deviates and densities.