Most commonly used distributions on the unit hypersphere Sk−1={v∈Rk:v⊤v=1}, k≥2, assume that the data are rotationally symmetric about some direction θ∈Sk−1. However, there is empirical evidence that this assumption often fails to describe reality. We study in this paper a new class of skew-rotationally-symmetric distributions on Sk−1 that enjoy numerous good properties. We discuss the Fisher information structure of the model and derive efficient inferential procedures. In particular, we obtain the first semi-parametric test for rotational symmetry about a known direction. We also propose a second test for rotational symmetry, obtained through the definition of a new measure of skewness on the hypersphere. We investigate the finite-sample ...
In this article a semi-parametric class of skew-symmetric distributions is considered. We call this ...
Rotationally symmetric distributions on the unit hyperpshere are among the most commonly met in dire...
peer reviewedThis paper presents Bayesian directional data modeling via the skew-rotationally-symmet...
peer reviewedMost commonly used distributions on the unit hypersphere Sk−1={v∈Rk:v⊤v=1}, k≥2, assume...
Motivated by the central role played by rotationally symmetric distributions in directional statisti...
Motivated by the central role played by rotationally symmetric distributions in directional statisti...
peer reviewedA classical characterization result, which can be traced back to Gauss, states that the...
In this paper we propose optimal tests for circular reflective symmetry about a fixed median directi...
In this paper, we propose optimal tests for reflective circular symmetry about a fixed median direct...
We define a distribution on the unit sphere Sd−1 called the elliptically symmetric angular Gaussian ...
In the first part of this thesis we consider the skew-normal class of distributions on the line and ...
For a general class of unipolar, rotationally symmetric distributions on the multi-dimensional unit ...
In this paper, we provide R-estimators of the location of a rotationally symmetric distribution on t...
In this paper, we provide R-estimators of the location of a rotationally symmetric distribution on t...
In this article, we study some results related to a specific class of distributions, called skew-cur...
In this article a semi-parametric class of skew-symmetric distributions is considered. We call this ...
Rotationally symmetric distributions on the unit hyperpshere are among the most commonly met in dire...
peer reviewedThis paper presents Bayesian directional data modeling via the skew-rotationally-symmet...
peer reviewedMost commonly used distributions on the unit hypersphere Sk−1={v∈Rk:v⊤v=1}, k≥2, assume...
Motivated by the central role played by rotationally symmetric distributions in directional statisti...
Motivated by the central role played by rotationally symmetric distributions in directional statisti...
peer reviewedA classical characterization result, which can be traced back to Gauss, states that the...
In this paper we propose optimal tests for circular reflective symmetry about a fixed median directi...
In this paper, we propose optimal tests for reflective circular symmetry about a fixed median direct...
We define a distribution on the unit sphere Sd−1 called the elliptically symmetric angular Gaussian ...
In the first part of this thesis we consider the skew-normal class of distributions on the line and ...
For a general class of unipolar, rotationally symmetric distributions on the multi-dimensional unit ...
In this paper, we provide R-estimators of the location of a rotationally symmetric distribution on t...
In this paper, we provide R-estimators of the location of a rotationally symmetric distribution on t...
In this article, we study some results related to a specific class of distributions, called skew-cur...
In this article a semi-parametric class of skew-symmetric distributions is considered. We call this ...
Rotationally symmetric distributions on the unit hyperpshere are among the most commonly met in dire...
peer reviewedThis paper presents Bayesian directional data modeling via the skew-rotationally-symmet...