Flatness of location-scale-shape models under the Wasserstein metric

Abstract In Wasserstein geometry, one-dimensional location–scale models are flat both intrinsically and extrinsically—that is, they are curvature-free as well as totally geodesic in the space of probability distributions. In this study, we introduce a class of one-dimensional statistical models, termed the location–scale–shape model, which generalizes several distributions used in extreme-value theory. This model has a shape parameter that specifies the tail heaviness. We investigate the Wasserstein geometry of the location-scale-shape model and show that it is intrinsically flat but extrinsically curved.