boostmtree: Boosted Multivariate Trees for Longitudinal Data

Implements Friedman's gradient descent boosting algorithm for modeling of continuous or binary longitudinal response using multivariate tree base learners. A time-covariate interaction effect is modeled using penalized B-splines (P-splines) with estimated adaptive smoothing parameter.

Version: 1.4.1
Depends: R (≥ 3.5.0)
Imports: randomForestSRC (≥ 2.9.0), parallel, splines, nlme
Published: 2019-11-21
Author: Hemant Ishwaran, Amol Pande
Maintainer: Udaya B. Kogalur <ubk at>
License: GPL (≥ 3)
NeedsCompilation: no
Citation: boostmtree citation info
Materials: NEWS
CRAN checks: boostmtree results


Reference manual: boostmtree.pdf
Package source: boostmtree_1.4.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: boostmtree_1.4.1.tgz, r-oldrel: boostmtree_1.4.1.tgz
Old sources: boostmtree archive


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