regMMD

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. doi:10.1093/biomet/asad031 doi:10.3150/21-BEJ1338.

Last 30 days

This package has been downloaded 369 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 2,479 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Apr 01, 2025 with 54 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.