# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "pblm" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'pblm: Bivariate Additive Marginal Logistic Regression via Maximum Penalized
  Likelihood Estimation'
version: 0.1-8
doi: 10.32614/CRAN.package.pblm
abstract: Bivariate additive categorical regression for moderate-to-small size datasets.
  Under a multinomial scheme, it is possible to fit bivariate models when the two
  responses are nominal, ordinal or mixed nominal/ordinal. Partial proportional odds
  models with (non-)uniform association structure can be fitted with the possibility
  to specify several logit types and parametrizations for the marginals and the association,
  including the Dale's model. The association structure can also be smoothed using
  penalty terms of polynomial type. P-splines are used in the additive part of the
  model. Common methods such as summary, residuals and predict are available.
authors:
- family-names: Enea
  given-names: Marco
  email: marco.enea@unipa.it
- family-names: Stasinopoulos
  given-names: with contributions by Mikis
- family-names: Rigby
  given-names: Robert
repository: https://marcoenea.r-universe.dev
repository-code: http://github.com/enea/pblm
commit: 1e77d719ceee6a734f1e1cb9e627a174ac3c81b9
url: http://github.com/enea/pblm
date-released: '2017-04-02'
contact:
- family-names: Enea
  given-names: Marco
  email: marco.enea@unipa.it