# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "BART" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'BART: Bayesian Additive Regression Trees'
version: 2.9.9
doi: 10.18637/jss.v097.i01
identifiers:
- type: doi
  value: 10.32614/CRAN.package.BART
abstract: Bayesian Additive Regression Trees (BART) provide flexible nonparametric
  modeling of covariates for continuous, binary, categorical and time-to-event outcomes.
  For more information see Sparapani, Spanbauer and McCulloch <https://doi.org/10.18637/jss.v097.i01>.
authors:
- family-names: McCulloch
  given-names: Robert
- family-names: Sparapani
  given-names: Rodney
  email: rsparapa@mcw.edu
preferred-citation:
  type: article
  title: 'Nonparametric Machine Learning and Efficient Computation with Bayesian Additive
    Regression Trees: The BART R Package'
  authors:
  - family-names: Sparapani
    given-names: Rodney
    email: rsparapa@mcw.edu
  - family-names: Spanbauer
    given-names: Charles
  - family-names: McCulloch
    given-names: Robert
  journal: Journal of Statistical Software
  year: '2021'
  volume: '97'
  issue: '1'
  doi: 10.18637/jss.v097.i01
  start: '1'
  end: '66'
repository: https://rsparapa.r-universe.dev
commit: 4e177d08a14581ffa25a83b9dde35dfcc8057522
date-released: '2024-06-21'
contact:
- family-names: Sparapani
  given-names: Rodney
  email: rsparapa@mcw.edu