Corpus ID: 212725185

Multivariate Goodness-of-Fit Tests Based on Wasserstein Distance

@article{Hallin2020MultivariateGT,
  title={Multivariate Goodness-of-Fit Tests Based on Wasserstein Distance},
  author={M. Hallin and Gilles Mordant and Johan Segers},
  journal={arXiv: Methodology},
  year={2020}
}
Goodness-of-fit tests based on the empirical Wasserstein distance are proposed for simple and composite null hypotheses involving general multivariate distributions. This includes the important problem of testing for multivariate normality with unspecified location and covariance and, more generally, testing for elliptical symmetry with given standard radial density, unspecified location and scatter parameters. The calculation of test statistics boils down to solving the well-studied semi… Expand
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