Package: boostmtree
Version: 1.5.0
Date: 2020-11-23
Title: Boosted Multivariate Trees for Longitudinal Data
Author: Hemant Ishwaran <hemant.ishwaran@gmail.com>, Amol Pande <amoljpande@gmail.com>
Maintainer: Udaya B. Kogalur <ubk@kogalur.com>
Depends: R (>= 3.5.0)
Imports: randomForestSRC (>= 2.9.0), parallel, splines, nlme
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 <DOI:10.1007/s10994-016-5597-1>. 
License: GPL (>= 3)
URL: http://web.ccs.miami.edu/~hishwaran/
NeedsCompilation: no
Packaged: 2020-11-23 17:59:59 UTC; kogalur
Repository: CRAN
Date/Publication: 2020-11-24 07:50:10 UTC
