# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "mlt" in publications use:'
type: software
license: GPL-2.0-only
title: 'mlt: Most Likely Transformations'
version: 1.6-1
identifiers:
- type: doi
  value: 10.32614/CRAN.package.mlt
abstract: Likelihood-based estimation of conditional transformation models via the
  most likely transformation approach described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>
  and Hothorn (2020) <DOI:10.18637/jss.v092.i01>. Shift-scale (Siegfried et al, 2023,
  <DOI:10.1080/00031305.2023.2203177>) and multivariate (Klein et al, 2022, <DOI:10.1111/sjos.12501>)
  transformation models are part of this package. A package vignette is available
  from <DOI:10.32614/CRAN.package.mlt.docreg> and more convenient user interfaces
  to many models from <DOI:10.32614/CRAN.package.tram>.
authors:
- family-names: Hothorn
  given-names: Torsten
  email: Torsten.Hothorn@R-project.org
  orcid: https://orcid.org/0000-0001-8301-0471
preferred-citation:
  type: article
  title: Most Likely Transformations
  authors:
  - family-names: Hothorn
    given-names: Torsten
    email: Torsten.Hothorn@R-project.org
    orcid: https://orcid.org/0000-0001-8301-0471
  - family-names: Möst
    given-names: Lisa
  - family-names: Bühlmann
    given-names: Peter
  journal: Scandinavian Journal of Statistics
  year: '2018'
  volume: '45'
  issue: '1'
  start: '110'
  end: '134'
repository: https://r-forge.r-universe.dev
commit: 1bc316d3663331cbad8870e18244df530886f0fa
url: http://ctm.R-forge.R-project.org
date-released: '2024-11-01'
contact:
- family-names: Hothorn
  given-names: Torsten
  email: Torsten.Hothorn@R-project.org
  orcid: https://orcid.org/0000-0001-8301-0471
references:
- type: article
  title: 'Most Likely Transformations: The mlt Package'
  authors:
  - name: Torsten Hothorn
  journal: Journal of Statistical Software
  year: '2020'
  volume: '92'
  issue: '1'
  doi: 10.18637/jss.v092.i01
  start: '1'
  end: '68'