# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- 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) Cherief-Abdellatif, B.-E. and Alquier, P. (2022) .' 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