Installation
About
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.
Citation | boostmtree citation info |
ishwaran.org/ishwaran.html |
Key Metrics
Downloads
Yesterday | 7 0% |
Last 7 days | 65 -20% |
Last 30 days | 338 -12% |
Last 90 days | 1.029 -11% |
Last 365 days | 4.091 -15% |