print.boostmtree

An object of class <code>(boostmtree, grow)</code> or <code>(boostmtree,
	predict)</code>.

Further arguments passed to or from other methods.

Print summary output from the boosting analysis.

print

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>.

print.boostmtree: Print Summary Output

Description

Usage

Arguments

References