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Main Authors: Schutte, Emily, Loizidou, Sophia, Laheurte, Vincent
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.04369
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author Schutte, Emily
Loizidou, Sophia
Laheurte, Vincent
author_facet Schutte, Emily
Loizidou, Sophia
Laheurte, Vincent
contents Skewed distributions are fundamental in modelling asymmetric data on the d-dimensional torus. In this context, asymmetry is introduced through the sine-skewing mechanism, which is the only skewing mechanism that has been proposed on the hyper-torus in the literature. Some sine-skewed models are known to suffer from a singular Fisher information matrix in the vicinity of symmetry, which poses a significant issue for inferential purposes. It is an open question to determine for which sine-skewed models Fisher information singularity occurs. In this paper, a general characterization of the class of models that exhibit this singularity is given in the general d-dimensional setting.
format Preprint
id arxiv_https___arxiv_org_abs_2603_04369
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle On the singularity of the Fisher Information matrix in the sine-skewed family on the d-dimensional torus
Schutte, Emily
Loizidou, Sophia
Laheurte, Vincent
Statistics Theory
Skewed distributions are fundamental in modelling asymmetric data on the d-dimensional torus. In this context, asymmetry is introduced through the sine-skewing mechanism, which is the only skewing mechanism that has been proposed on the hyper-torus in the literature. Some sine-skewed models are known to suffer from a singular Fisher information matrix in the vicinity of symmetry, which poses a significant issue for inferential purposes. It is an open question to determine for which sine-skewed models Fisher information singularity occurs. In this paper, a general characterization of the class of models that exhibit this singularity is given in the general d-dimensional setting.
title On the singularity of the Fisher Information matrix in the sine-skewed family on the d-dimensional torus
topic Statistics Theory
url https://arxiv.org/abs/2603.04369