Estimating geometric anisotropy in spatial point patterns
Artikel i vetenskaplig tidskrift, 2016

Anisotropy in stationary spatial point patterns is investigated. We develop a two-stage non-parametric method for quantifying geometric anisotropy arising for example when the pattern is compressed or stretched. First, we fit ellipsoids to the pattern of pairwise difference vectors to estimate the direction of anisotropy. Then, we estimate the scale of anisotropy by identifying the back-transformation resulting in the most isotropic pattern. We demonstrate the applicability of the method mainly for regular patterns by numerical examples, and use it to improve the estimation of compression in 3D polar ice air bubble patterns.

Non-parametric statistics

Anisotropy

Polar ice

Spatial point process

Ellipsoid

Författare

Tuomas Rajala

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Matematisk statistik

Aila Särkkä

Chalmers, Matematiska vetenskaper, Matematisk statistik

Göteborgs universitet

Claudia Redenbach

Technische Universität Kaiserslautern

Martina Sormani

Fraunhofer-Gesellschaft

Technische Universität Kaiserslautern

Spatial Statistics

2211-6753 (ISSN)

Vol. 15 100-114

Ämneskategorier (SSIF 2011)

Matematik

Geologi

DOI

10.1016/j.spasta.2015.12.005

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Senast uppdaterat

2025-03-08