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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "RegEnRF" in publications use:'
type: software
license: MIT
title: 'RegEnRF: Regression-Enhanced Random Forests'
version: 1.0.0.9000
identifiers:
- type: doi
  value: 10.32614/CRAN.package.RegEnRF
abstract: A novel generalized Random Forest method, that can improve on RFs by borrowing
  the strength of penalized parametric regression. Based on Zhang et al. (2019) <https://doi.org/10.48550/arXiv.1904.10416>.
authors:
- family-names: Minora
  given-names: Umberto
  email: umbertofilippo@tiscali.it
  orcid: https://orcid.org/0000-0003-2151-6500
preferred-citation:
  type: generic
  title: Regression-Enhanced Random Forests
  authors:
  - family-names: Zhang
    given-names: Haozhe
  - family-names: Nettleton
    given-names: Dan
  - family-names: Zhu
    given-names: Zhengyuan
  year: '2019'
  url: https://arxiv.org/abs/1904.10416
repository: https://umbe1987.r-universe.dev
repository-code: https://github.com/umbe1987/regenrf
commit: 802995fd790c817ae5fbe6053e449a02bd5e058f
url: https://github.com/umbe1987/regenrf
date-released: '2026-03-26'
contact:
- family-names: Minora
  given-names: Umberto
  email: umbertofilippo@tiscali.it
  orcid: https://orcid.org/0000-0003-2151-6500