threeboost package implements a the EEBoost algorithm described in Wolfson (2011, JASA).
EEBoost is a general-purpose method for variable selection which can be applied whenever inference would be based on an estimating equation.
Thresholded EEBoost (function threeboost) is a generalization of EEBoost which allows multiple variables to enter the model at each boosting step.
EEBoost (function eeboost) is a special case of thresholded boosting with the threshold set to 1.The package currently provides a "pre-packaged" function, geeboost, which carries out
variable selection for correlated outcome data based on the Generalized Estimating Equations. However,
the threeboost (and eeboost) functions can also accommodate user-provided estimating functions.