Thresholded variable selection and prediction based on
estimating equations
Description
This package implements a thresholded version of 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. The package currently implements
variable selection based on the Generalized Estimating Equations, but can
also accommodate user-provided estimating functions. Thresholded EEBoost is
a generalization which allows multiple variables to enter the model at each
boosting step.