Historical Tree Ensembles for Longitudinal Data
Description
Historical regression trees are an extension of standard trees,
producing a non-parametric estimate of how the response depends on
all of its prior realizations as well as that of any time-varying predictor
variables. The method applies equally to regularly as well as irregularly
sampled data. The package implements random forest and boosting ensembles
based on historical regression trees, suitable for longitudinal data.
Standard error estimation and Z-score variable importance is also implemented.