threeboost: Thresholded variable selection and prediction based on estimating equations

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.

Install the latest version of this package by entering the following in R:
install.packages("threeboost")
AuthorJulian Wolfson and Christopher Miller
Date of publication2014-08-11 00:18:02
MaintainerJulian Wolfson <julianw@umn.edu>
LicenseGPL-3
Version1.1

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Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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