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
| Version | Repository | File | Size |
|---|---|---|---|
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
- Rdpack (>= 0.7)