threeboost: Thresholded variable selection and prediction based on estimating equations
Version 1.1

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

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threeboost documentation built on May 29, 2017, 3:47 p.m.