GPLTR: Generalized Partially Linear Tree-Based Regression Model
Combining a generalized linear model with an additional tree part
on the same scale. A four-step procedure is proposed to fit the model and test
the joint effect of the selected tree part while adjusting on confounding factors.
We also proposed an ensemble procedure based on the bagging to improve prediction
accuracy and computed several scores of importance for variable selection.
See 'Cyprien Mbogning et al.'(2014)<doi:10.1186/2043-9113-4-6> and
'Cyprien Mbogning et al.'(2015)<doi:10.1159/000380850>
for an overview of all the methods implemented in this package.
||rpart , parallel
||Cyprien Mbogning and Wilson Toussile
||Cyprien Mbogning <cyprien.mbogning at gmail.com>
||GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
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