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.

Package details

AuthorJulian Wolfson and Christopher Miller
MaintainerJulian Wolfson <>
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the threeboost package in your browser

Any scripts or data that you put into this service are public.

threeboost documentation built on May 2, 2019, 2:37 a.m.