person("Marjolein", "Fokkema", role = c("aut", "cre"), email =
"m.fokkema@fsw.leidenuniv.nl")
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 a prediction rule ensemble. Functions print(),
plot(), coef() and importance() can be used to inspect the generated ensemble.
Function predict() generates predicted values. Functions singeplot() and
pairplot() depict dependence of the output on specified predictor variables.
Function cvpre() performs full cross validation of a pre to calculate the
expected prediction error. Functions interact() and bsnullinteract() can be
used to assess interaction effects of predictor variables.
R (>= 3.1.0), partykit, glmnet, MatrixModels, Formula,
methods, graphics

c(person("Marjolein", "Fokkema", role = c("aut", "cre"), email =
"m.fokkema@fsw.leidenuniv.nl"), person(given = "Benjamin",
family = "Christoffersen", role = "aut", email = "boennecd@gmail.com"))
Marjolein Fokkema [aut, cre], Benjamin Christoffersen [aut]
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.
glmnet, MatrixModels, Formula, methods, graphics, partykit,
earth, stringr
akima, grid, foreach, testthat, mlbench, datasets

Marjolein Fokkema [aut, cre],
Benjamin Christoffersen [aut]

Derives prediction rule ensembles (PREs). Largely follows the
procedure for deriving PREs as described in Friedman & Popescu (2008;
<DOI:10.1214/07-AOAS148>), with adjustments and improvements. The
main function pre() derives prediction rule ensembles consisting of
rules and/or linear terms for continuous, binary, count, multinomial,
and multivariate continuous responses. Function gpe() derives
generalized prediction ensembles, consisting of rules, hinge and linear
functions of the predictor variables.
earth, Formula, glmnet, graphics, methods, partykit, rpart,
stringr
akima, datasets, doParallel, foreach, glmertree, grid,
mlbench, testthat