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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 "regMMD" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'regMMD: Robust Regression and Estimation Through Maximum Mean Discrepancy
  Minimization'
version: 0.0.1
doi: 10.32614/CRAN.package.regMMD
abstract: 'The functions in this package compute robust estimators by minimizing a
  kernel-based distance known as MMD (Maximum Mean Discrepancy) between the sample
  and a statistical model. Recent works proved that these estimators enjoy a universal
  consistency property, and are extremely robust to outliers. Various optimization
  algorithms are implemented: stochastic gradient is available for most models, but
  the package also allows gradient descent in a few models for which an exact formula
  is available for the gradient. In terms of distribution fit, a large number of continuous
  and discrete distributions are available: Gaussian, exponential, uniform, gamma,
  Poisson, geometric, etc. In terms of regression, the models available are: linear,
  logistic, gamma, beta and Poisson. Alquier, P. and Gerber, M. (2024) <https://doi.org/10.1093/biomet/asad031>
  Cherief-Abdellatif, B.-E. and Alquier, P. (2022) <https://doi.org/10.3150/21-BEJ1338>.'
authors:
- family-names: Alquier
  given-names: Pierre
  email: pierre.alquier.stat@gmail.com
  orcid: https://orcid.org/0000-0003-4249-7337
- family-names: Gerber
  given-names: Mathieu
  email: mathieu.gerber@bristol.ac.uk
  orcid: https://orcid.org/0000-0001-6774-2330
repository: https://CRAN.R-project.org/package=regMMD
date-released: '2024-10-25'
contact:
- family-names: Alquier
  given-names: Pierre
  email: pierre.alquier.stat@gmail.com
  orcid: https://orcid.org/0000-0003-4249-7337