We consider the problem of testing uniformity on high-dimensional unit spheres.We are primarily interested in nonnull issues.We show that rotationally symmetric alternatives lead to two Local Asymptotic Normality (LAN) structures. The first one is for fixed modal location θ and allows to derive locally asymptotically most powerful tests under specified θ. The second one, that addresses the Fisher-von Mises-Langevin (FvML) case, relates to the unspecified-θ problem and shows that the high-dimensional Rayleigh test is locally asymptotically most powerful invariant. Under mild assumptions, we derive the asymptotic nonnull distribution of this test, which allows to extend away from the FvML case the asymptotic powers obtained there from Le Cam'...
In this paper we tackle the problem of testing the homogeneity of concentrations for directional dat...
We consider asymptotic inference for the concentration of directional data. More precisely, wepropos...
The general machinery of Cordeiro and Ferrari (1991. Biometrika 78. 573-582) and Chandra and Mukerje...
Testing uniformity on the p-dimensional unit sphere is arguably the most fundamental problem in dire...
Circular and spherical data arise in many applications, especially in biology, Earth sciences and as...
AbstractThe Grassmann manifold Gk,m − k consists of k-dimensional linear subspaces V in Rm. To each ...
This paper mainly focuses on one of the most classical testing problems in directional statistics, n...
One-sample and multi-sample tests on the concentration parameter of Fisher-von Mises-Langevin distri...
Rotationally symmetric distributions on the unit hyperpshere are among the most commonly met in dire...
For a general class of unipolar, rotationally symmetric distributions on the multi-dimensional unit ...
Motivated by the central role played by rotationally symmetric distributions in directional statisti...
AbstractThe general machinery of Cordeiro and Ferrari (1991, Biometrika78, 573–582) and Chandra and ...
AbstractFor a general class of unipolar, rotationally symmetric distributions on the multi-dimension...
Let Xd be a real or complex Hilbert space of finite but large dimension d, let S(Xd ) denote the uni...
Let X be a real or complex Hilbert space of finite but large dimension d, let S(X) denote the unit s...
In this paper we tackle the problem of testing the homogeneity of concentrations for directional dat...
We consider asymptotic inference for the concentration of directional data. More precisely, wepropos...
The general machinery of Cordeiro and Ferrari (1991. Biometrika 78. 573-582) and Chandra and Mukerje...
Testing uniformity on the p-dimensional unit sphere is arguably the most fundamental problem in dire...
Circular and spherical data arise in many applications, especially in biology, Earth sciences and as...
AbstractThe Grassmann manifold Gk,m − k consists of k-dimensional linear subspaces V in Rm. To each ...
This paper mainly focuses on one of the most classical testing problems in directional statistics, n...
One-sample and multi-sample tests on the concentration parameter of Fisher-von Mises-Langevin distri...
Rotationally symmetric distributions on the unit hyperpshere are among the most commonly met in dire...
For a general class of unipolar, rotationally symmetric distributions on the multi-dimensional unit ...
Motivated by the central role played by rotationally symmetric distributions in directional statisti...
AbstractThe general machinery of Cordeiro and Ferrari (1991, Biometrika78, 573–582) and Chandra and ...
AbstractFor a general class of unipolar, rotationally symmetric distributions on the multi-dimension...
Let Xd be a real or complex Hilbert space of finite but large dimension d, let S(Xd ) denote the uni...
Let X be a real or complex Hilbert space of finite but large dimension d, let S(X) denote the unit s...
In this paper we tackle the problem of testing the homogeneity of concentrations for directional dat...
We consider asymptotic inference for the concentration of directional data. More precisely, wepropos...
The general machinery of Cordeiro and Ferrari (1991. Biometrika 78. 573-582) and Chandra and Mukerje...