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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 "ppgmmga" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'ppgmmga: Projection Pursuit Based on Gaussian Mixtures and Evolutionary Algorithms'
version: '1.3'
doi: 10.1080/10618600.2019.1598871
identifiers:
- type: doi
  value: 10.32614/CRAN.package.ppgmmga
abstract: Projection Pursuit (PP) algorithm for dimension reduction based on Gaussian
  Mixture Models (GMMs) for density estimation using Genetic Algorithms (GAs) to maximise
  an approximated negentropy index. For more details see Scrucca and Serafini (2019)
  <https://doi.org/10.1080/10618600.2019.1598871>.
authors:
- family-names: Serafini
  given-names: Alessio
  email: srf.alessio@gmail.com
  orcid: https://orcid.org/0000-0002-8579-5695
- family-names: Scrucca
  given-names: Luca
  email: luca.scrucca@unipg.it
  orcid: https://orcid.org/0000-0003-3826-0484
preferred-citation:
  type: article
  title: Projection pursuit based on Gaussian mixtures and evolutionary algorithms
  authors:
  - family-names: Scrucca
    given-names: Luca
    email: luca.scrucca@unipg.it
    orcid: https://orcid.org/0000-0003-3826-0484
  - family-names: Serafini
    given-names: Alessio
    email: srf.alessio@gmail.com
    orcid: https://orcid.org/0000-0002-8579-5695
  journal: Journal of Computational and Graphical Statistics
  year: '2019'
  volume: '28'
  issue: '4'
  doi: 10.1080/10618600.2019.1598871
  start: 847–-860
repository: https://CRAN.R-project.org/package=ppgmmga
repository-code: https://github.com/luca-scr/ppgmmga
url: https://github.com/luca-scr/ppgmmga
date-released: '2023-11-17'
contact:
- family-names: Scrucca
  given-names: Luca
  email: luca.scrucca@unipg.it
  orcid: https://orcid.org/0000-0003-3826-0484