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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 "opGMMassessment" in publications use:'
type: software
license: GPL-3.0-only
title: 'opGMMassessment: Optimized Automated Gaussian Mixture Assessment'
version: 0.4.5
doi: 10.1016/j.imu.2022.101113
identifiers:
- type: doi
  value: 10.32614/CRAN.package.opGMMassessment
abstract: Necessary functions for optimized automated evaluation of the number and
  parameters of Gaussian mixtures in one-dimensional data. Various methods are available
  for parameter estimation and for determining the number of modes in the mixture.
  A detailed description of the methods ca ben found in Lotsch, J., Malkusch, S. and
  A. Ultsch. (2022) <https://doi.org/10.1016/j.imu.2022.101113>.
authors:
- family-names: Lotsch
  given-names: Jorn
  email: j.lotsch@em.uni-frankfurt.de
  orcid: https://orcid.org/0000-0002-5818-6958
- family-names: Malkusch
  given-names: Sebastian
  orcid: https://orcid.org/0000-0001-6766-140X
preferred-citation:
  type: article
  title: Comparative assessment of automated algorithms for the separation of one-dimensional
    Gaussian mixtures
  authors:
  - family-names: Lötsch
    given-names: Jörn
  - family-names: Malkusch
    given-names: Sebastian
    orcid: https://orcid.org/0000-0001-6766-140X
  - family-names: Ultsch
    given-names: Alfred
  journal: Informatics in Medicine Unlocked
  volume: '34'
  year: '2022'
  issn: 2352-9148
  doi: 10.1016/j.imu.2022.101113
  url: https://doi.org/10.1016/j.imu.2022.101113
  start: '101113'
repository: https://jornlotsch.r-universe.dev
repository-code: https://github.com/JornLotsch/opGMMassessment
commit: dcf9080b136a7ab55a3e95c1789533305f598efd
url: https://github.com/JornLotsch/opGMMassessment
date-released: '2026-04-17'
contact:
- family-names: Lotsch
  given-names: Jorn
  email: j.lotsch@em.uni-frankfurt.de
  orcid: https://orcid.org/0000-0002-5818-6958