Implements Friedman's gradient descent boosting algorithm for longitudinal data using multivariate tree base learners. A time-covariate interaction effect is modeled using penalized B-splines (P-splines) with estimated adaptive smoothing parameter.
| Version: | 1.3.0 |
| Depends: | R (≥ 3.1.0) |
| Imports: | randomForestSRC (≥ 2.5.0), parallel, splines, nlme |
| Published: | 2018-08-13 |
| Author: | Hemant Ishwaran, Amol Pande |
| Maintainer: | Udaya B. Kogalur <ubk at kogalur.com> |
| License: | GPL (≥ 3) |
| URL: | http://web.ccs.miami.edu/~hishwaran http://www.kogalur.com |
| NeedsCompilation: | no |
| Citation: | boostmtree citation info |
| Materials: | NEWS |
| CRAN checks: | boostmtree results |
| Reference manual: | boostmtree.pdf |
| Package source: | boostmtree_1.3.0.tar.gz |
| Windows binaries: | r-devel: boostmtree_1.3.0.zip, r-release: boostmtree_1.3.0.zip, r-oldrel: boostmtree_1.3.0.zip |
| OS X binaries: | r-release: boostmtree_1.3.0.tgz, r-oldrel: boostmtree_1.3.0.tgz |
| Old sources: | boostmtree archive |
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