Package: threeboost
Type: Package
Title: Thresholded variable selection and prediction based on
        estimating equations
Version: 1.1
Date: 2014-08-09
Author: Julian Wolfson and Christopher Miller
Maintainer: Julian Wolfson <julianw@umn.edu>
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.
License: GPL-3
Imports: Matrix
Suggests: mvtnorm
Packaged: 2014-08-09 14:26:54 UTC; Julian
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-08-11 00:18:02
