Imports: dplyr, tidyr, ggplot2, tibble, irr, lpSolve, purrr, class,

Authors@R: person("Marjolein", "Fokkema", role = c("aut", "cre"), email = "m.fokkema@fsw.leidenuniv.nl")
Description: 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 coef() and
importance() can be used to inspect the generated ensemble. Function predict()
generates predicted values. 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
Depends: R (>= 3.3.0), partykit, glmnet, MatrixModels, Formula,

Authors@R: person("Marjolein", "Fokkema", role = c("aut", "cre"), email =
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.
Depends: R (>= 3.1.0), partykit, glmnet, MatrixModels, Formula,

Authors@R: c(person("Marjolein", "Fokkema", role = c("aut", "cre"), email =
family = "Christoffersen", role = "aut", email = "boennecd@gmail.com"))
Author: Marjolein Fokkema [aut, cre], Benjamin Christoffersen [aut]
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.
Imports: glmnet, MatrixModels, Formula, methods, graphics, partykit,
Suggests: akima, grid, foreach, testthat, mlbench, datasets