predict.gpe

of class <code><a rd-options="" href="/link/gpe?package=pre&version=0.3.0" data-mini-rdoc="pre::gpe">gpe</a></code>

object

optional new data to compute predictions for

newdata

argument passed to <code><a rd-options="" href="/link/predict.cv.glmnet?package=pre&version=0.3.0" data-mini-rdoc="pre::predict.cv.glmnet">predict.cv.glmnet</a></code>

type

argument passed to <code>s</code> argument of <code><a rd-options="" href="/link/predict.cv.glmnet?package=pre&version=0.3.0" data-mini-rdoc="pre::predict.cv.glmnet">predict.cv.glmnet</a></code>

penalty.par.val

Predict function for <code><a rd-options="" href="/link/gpe?package=pre&version=0.3.0" data-mini-rdoc="pre::gpe">gpe</a></code>

Derives prediction rule ensembles (PREs). Largely follows the
procedure for deriving PREs as described in Friedman & Popescu (2008;
<DOI:10.1214/07-AOAS148>), with several adjustments and improvements. The
main function pre() derives prediction rule ensembles consisting of rules
and/or linear terms for binary, count and continuous responses. Function
gpe() derives generalized prediction ensembles, consisting of rules, hinge
and linear functions of the predictor variables.

Marjolein Fokkema

Prediction Rule Ensembles

Benjamin Christoffersen

predict.gpe function

of class <code><a rd-options='' href='gpe'>gpe</a></code>

argument passed to <code><a rd-options='' href='predict.cv.glmnet'>predict.cv.glmnet</a></code>

argument passed to <code>s</code> argument of <code><a rd-options='' href='predict.cv.glmnet'>predict.cv.glmnet</a></code>

Predict function for <code><a rd-options='' href='gpe'>gpe</a></code>

predict.gpe: Predicted Values Based on gpe Ensemble

Description

Usage

Arguments

Details

See Also