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regMMD

Robust Regression and Estimation Through Maximum Mean Discrepancy Minimization

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) <doi:10.1093/biomet/asad031> Cherief-Abdellatif, B.-E. and Alquier, P. (2022) <doi:10.3150/21-BEJ1338>.

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 regMMD_0.1.0.tar.gz 292.5 KiB
0.1.0 rolling linux/noble R-4.5 regMMD_0.1.0.tar.gz 292.5 KiB
0.1.0 rolling source/ R- regMMD_0.1.0.tar.gz 66.0 KiB
0.1.0 latest linux/jammy R-4.5 regMMD_0.1.0.tar.gz 292.5 KiB
0.1.0 latest linux/noble R-4.5 regMMD_0.1.0.tar.gz 292.5 KiB
0.1.0 latest source/ R- regMMD_0.1.0.tar.gz 66.0 KiB
0.1.0 2026-04-26 source/ R- regMMD_0.1.0.tar.gz 66.0 KiB
0.1.0 2026-04-23 source/ R- regMMD_0.1.0.tar.gz 66.0 KiB
0.1.0 2026-04-09 windows/windows R-4.5 regMMD_0.1.0.zip 294.3 KiB
0.0.1 2025-04-20 source/ R- regMMD_0.0.1.tar.gz 64.8 KiB

Dependencies (latest)

Imports