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The Maximum Mean Discrepancy (MMD) is a kernel-based metric widely used fornonparametric tests and estimation. Recently, it has also been studied as anobjective function for parametric estimation, as it has been shown to yieldrobust estimators. We have implemented MMD minimization for parameter inferencein a wide range of statistical models, including various regression models,within an R package called regMMD. This paper provides an introduction to theregMMD package. We describe the available kernels and optimization procedures,as well as the default settings. Detailed applications to simulated and realdata are provided.

regMMD: An R package for parametric estimation and regression with maximum mean discrepancy