AbstractA general class of optimal and distribution-free rank tests for the two-sample modal directions problem on (hyper-) spheres is proposed, along with an asymptotic distribution theory for such spherical rank tests. The asymptotic optimality of the spherical rank tests in terms of power-equivalence to the spherical likelihood ratio tests is studied, while the spherical Wilcoxon rank test, an important case for the class of spherical rank tests, is further investigated. A data set is reanalyzed and some errors made in previous studies are corrected. On the usual sphere, a lower bound on the asymptotic Pitman relative efficiency relative to Hotelling’s T2-type test is established, and a new distribution for which the spherical Wilcoxon r...
Motivated by the central role played by rotationally symmetric distributions in directional statisti...
We consider a test for spherical symmetry of a distribution in dwith an unknown center. It is a mult...
This paper mainly focuses on one of the most classical testing problems in directional statistics, n...
AbstractFor a general class of unipolar, rotationally symmetric distributions on the multi-dimension...
We tackle the classical two-sample spherical location problem for directional data by having recours...
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 ...
Abstract. We generalize signed rank statistics to dimensions higher than one. This results in a clas...
In this paper we tackle the problem of testing the homogeneity of concentrations for directional dat...
There are at least two reasons for a symmetric, unimodal, diffuse tailed hyperbolic secant distribut...
We consider the problem of testing uniformity on high-dimensional unit spheres.We are primarily inte...
Testing uniformity on the p-dimensional unit sphere is arguably the most fundamental problem in dire...
Nonparametric procedures for testing and estimation of the shape matrix in the case of multivariate ...
Recently, Verdebout (2015) introduced a Kruskal–Wallis type rank-based procedure ϕV (n) to test the ...
AbstractWe consider a test for spherical symmetry of a distribution in Rdwith an unknown center. It ...
Motivated by the central role played by rotationally symmetric distributions in directional statisti...
We consider a test for spherical symmetry of a distribution in dwith an unknown center. It is a mult...
This paper mainly focuses on one of the most classical testing problems in directional statistics, n...
AbstractFor a general class of unipolar, rotationally symmetric distributions on the multi-dimension...
We tackle the classical two-sample spherical location problem for directional data by having recours...
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 ...
Abstract. We generalize signed rank statistics to dimensions higher than one. This results in a clas...
In this paper we tackle the problem of testing the homogeneity of concentrations for directional dat...
There are at least two reasons for a symmetric, unimodal, diffuse tailed hyperbolic secant distribut...
We consider the problem of testing uniformity on high-dimensional unit spheres.We are primarily inte...
Testing uniformity on the p-dimensional unit sphere is arguably the most fundamental problem in dire...
Nonparametric procedures for testing and estimation of the shape matrix in the case of multivariate ...
Recently, Verdebout (2015) introduced a Kruskal–Wallis type rank-based procedure ϕV (n) to test the ...
AbstractWe consider a test for spherical symmetry of a distribution in Rdwith an unknown center. It ...
Motivated by the central role played by rotationally symmetric distributions in directional statisti...
We consider a test for spherical symmetry of a distribution in dwith an unknown center. It is a mult...
This paper mainly focuses on one of the most classical testing problems in directional statistics, n...