_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-pre 1.0.8
Propagated dependencies: r-survival@3.8-3 r-stringr@1.5.1 r-rpart@4.1.24 r-partykit@1.2-24 r-matrixmodels@0.5-4 r-matrix@1.7-3 r-glmnet@4.1-8 r-formula@1.2-5 r-earth@5.3.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/marjoleinF/pre
Licenses: GPL 2 GPL 3
Synopsis: Prediction Rule Ensembles
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 adjustments and improvements described in Fokkema (2020; <DOI:10.18637/jss.v092.i12>) and Fokkema & Strobl (2020; <DOI:10.1037/met0000256>). The main function pre() derives prediction rule ensembles consisting of rules and/or linear terms for continuous, binary, count, multinomial, survival and multivariate continuous responses. Function gpe() derives generalized prediction ensembles, consisting of rules, hinge and linear functions of the predictor variables.

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