A note on the geodesic normal distribution on the sphere

This paper presents an alternative formulation of the geodesic normal distribution on the sphere, building on the work of Hauberg (2018). While the isotropic version of this distribution is naturally defined on the sphere, the anisotropic version requires projecting points from the sphere onto the tangent space. In contrast, our approach removes the dependence on the tangent space and defines the geodesic normal distribution directly on the sphere. Moreover, we demonstrate that the density contours of this distribution are exactly ellipses on the sphere, providing intriguing alternative characterizations for describing this locus of points.

Authors

Institutions

Publication Details

Journal
Statistics & Probability Letters
Published
2025-08-20
DOI
https://doi.org/10.1016/j.spl.2025.110532
Primary Topic
Morphological variations and asymmetry
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A note on the geodesic normal distribution on the sphere

Andrea Meilán-Vila, José E. Chacón
Statistics & Probability Letters
Morphological variations and asymmetry
article

A note on the geodesic normal distribution on the sphere

Andrea Meilán-Vila, José E. Chacón
article en

Abstract

This paper presents an alternative formulation of the geodesic normal distribution on the sphere, building on the work of Hauberg (2018). While the isotropic version of this distribution is naturally defined on the sphere, the anisotropic version requires projecting points from the sphere onto the tangent space. In contrast, our approach removes the dependence on the tangent space and defines the geodesic normal distribution directly on the sphere. Moreover, we demonstrate that the density contours of this distribution are exactly ellipses on the sphere, providing intriguing alternative characterizations for describing this locus of points.

Statistics & Probability LettersVol. 227
Universidad Carlos III de Madrid (ES), Universidad de Extremadura (ES)
Ministerio de Ciencia, Innovación y Universidades, Ministerio de Ciencia e Innovación
Openalex Percentile: Top 73%
Morphological variations and asymmetry
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.