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.
|Author||Julian Wolfson and Christopher Miller|
|Date of publication||2014-08-11 00:18:02|
|Maintainer||Julian Wolfson <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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