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boostmtree
View on CRAN: Click
here
Download and install boostmtree package within the R console
Install from CRAN:
install.packages("boostmtree")
Install from Github:
library("remotes")
install_github("cran/boostmtree") Install by package version:
library("remotes")
install_version("boostmtree", "2.0.0") Attach the package and use:
library("boostmtree")
Maintained by
Udaya B. Kogalur
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-03-17
Latest Update:
Description:
Implements Friedman's gradient descent boosting algorithm for modeling longitudinal response using multivariate tree base learners. Longitudinal response could be continuous, binary, nominal or ordinal. A time-covariate interaction effect is modeled using penalized B-splines (P-splines) with estimated adaptive smoothing parameter. Although the package is design for longitudinal data, it can handle cross-sectional data as well. Implementation details are provided in Pande et al. (2017), Mach Learn .
How to cite:
Udaya B. Kogalur (2016). boostmtree: Boosted Multivariate Trees for Longitudinal Data. R package version 2.0.0, https://cran.r-project.org/web/packages/boostmtree. Accessed 07 Jun. 2026.
Previous versions and publish date:
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Other R packages that boostmtree depends,
imports, suggests or enhances
Complete documentation for boostmtree
Functions, R codes and Examples using
the boostmtree R package
Some associated functions: AF . boostmtree.news . boostmtree . boostmtree_package . marginalPlot . partialPlot . plot.boostmtree . predict.boostmtree . print.boostmtree . simLong . spirometry . vimp.boostmtree . vimpPlot .
Some associated R codes: boostmtree.R . boostmtree.news.R . generic.predict.boostmtree.R . marginalPlot.R . partialPlot.R . plot.boostmtree.R . predict.boostmtree.R . print.boostmtree.R . simLong.R . utilities.R . vimp.boostmtree.R . vimpPlot.R . zzz.R . Full boostmtree package functions and examples
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