Mainstream statistical methodology is generally applicable to data observed in Euclidean
space. There are, however, numerous contexts of considerable scientific interest in which …

Spatial quantiles on the hypersphere Page 1 The Annals of Statistics 2023, Vol. 51, No. 5,
2221–2245 https://doi.org/10.1214/23-AOS2332 © Institute of Mathematical Statistics, 2023 …

A particularly challenging context for dimensionality reduction is multivariate circular data,
that is, data supported on a torus. Such kind of data appears, for example, in the analysis of …

On a projection-based class of uniformity tests on the hypersphere Page 1 Bernoulli 29(1), 2023,
181–204 https://doi.org/10.3150/21-BEJ1454 On a projection-based class of uniformity tests on …

This article proposes various nonparametric tools based on measure transportation for
directional data. We use optimal transports to define new notions of distribution and quantile …

Tools from optimal transport (OT) theory have recently been used to define a notion of
quantile function for directional data. In practice, regularization is mandatory for applications …

We use Stein characterizations to obtain new moment-type estimators for the parameters of
three classical spherical distributions (namely the Fisher-Bingham, the von Mises-Fisher …

This paper is related to the issue of the density estimation of observations with values in a
Riemannian submanifold. In this context, Henry and Rodriguez ((2009),'Kernel Density …

Societal Impact Statement Citrus are intrinsically connected to human health and culture,
preventing human diseases like scurvy and inspiring sacred rituals. Citrus fruits come in a …

Inference for spherical location under high concentration Page 1 The Annals of Statistics 2020,
Vol. 48, No. 5, 2982–2998 https://doi.org/10.1214/19-AOS1918 © Institute of Mathematical …