Zobrazeno 1 - 10
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pro vyhledávání: '"VERDEBOUT, THOMAS"'
This paper proposes various nonparametric tools based on measure transportation for directional data. We use optimal transports to define new notions of distribution and quantile functions on the hypersphere, with meaningful quantile contours and reg
Externí odkaz:
http://arxiv.org/abs/2212.10345
Publikováno v:
In Insurance Mathematics and Economics July 2024 117:130-139
We consider a class of symmetry hypothesis testing problems including testing isotropy on $\mathbb{R}^d$ and testing rotational symmetry on the hypersphere $\mathcal{S}^{d-1}$. For this class, we study the null and non-null behaviors of Sobolev tests
Externí odkaz:
http://arxiv.org/abs/2108.09874
Autor:
García-Portugués, Eduardo, de Micheaux, Pierre Lafaye, Meintanis, Simos G., Verdebout, Thomas
We introduce nonparametric tests of independence for bivariate circular data based on trigonometric moments. Our contributions lie in (i) proposing nonparametric tests that are locally and asymptotically optimal against bivariate cosine von Mises alt
Externí odkaz:
http://arxiv.org/abs/2104.14620
Autor:
Bernard, Gaspard, Verdebout, Thomas
Publikováno v:
In Econometrics and Statistics January 2024 29:252-260
Autor:
Bernard, Gaspard, Verdebout, Thomas
Publikováno v:
In Journal of Multivariate Analysis January 2024 199
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Testing uniformity on the $p$-dimensional unit sphere is arguably the most fundamental problem in directional statistics. In this paper, we consider this problem in the framework of axial data, that is, under the assumption that the $n$ observations
Externí odkaz:
http://arxiv.org/abs/1910.09391
Preliminary test estimation, which is a natural procedure when it is suspected a priori that the parameter to be estimated might take value in a submodel of the model at hand, is a classical topic in estimation theory. In the present paper, we establ
Externí odkaz:
http://arxiv.org/abs/1906.10967
Autor:
Paindaveine, Davy, Verdebout, Thomas
Motivated by the fact that circular or spherical data are often much concentrated around a location $\pmb\theta$, we consider inference about $\pmb\theta$ under "high concentration" asymptotic scenarios for which the probability of any fixed spherica
Externí odkaz:
http://arxiv.org/abs/1901.00359