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boostmtree  

Boosted Multivariate Trees for Longitudinal Data
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", "1.5.1")



Attach the package and use:
library("boostmtree")
Maintained by
Udaya B. Kogalur
[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 1.5.1, https://cran.r-project.org/web/packages/boostmtree. Accessed 14 Mar. 2026.
Previous versions and publish date:
1.0.0 (2016-03-17 18:59), 1.1.0 (2016-04-12 17:01), 1.2.0 (2017-09-05 15:49), 1.2.1 (2018-02-12 20:15), 1.3.0 (2018-08-13 20:20), 1.4.0 (2019-11-20 21:20), 1.4.1 (2019-11-21 23:40), 1.5.0 (2020-11-24 08:50), 1.5.1 (2022-03-10 10:40)
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Complete documentation for boostmtree
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