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.

Polar ice

Spatial point process

Anisotropy

Non-parametric statistics

Ellipsoid

Författare

Tuomas Rajala

Göteborgs universitet

Chalmers, Matematiska vetenskaper, matematisk statistik

Aila Särkkä

Göteborgs universitet

Chalmers, Matematiska vetenskaper, matematisk statistik

Claudia Redenbach

Technische Universität Kaiserslautern

Aila Särkkä

Technische Universität Kaiserslautern

Fraunhofer-Institut fur Techno- und Wirtschaftsmathematk

Spatial Statistics

2211-6753 (ISSN)

Vol. 15 100-114

Ämneskategorier

Matematik

Geologi

DOI

10.1016/j.spasta.2015.12.005