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
Anisotropy
Spatial point process
Ellipsoid
Non-parametric statistics
Författare
Tuomas Rajala
Chalmers, Matematiska vetenskaper, Matematisk statistik
Göteborgs universitet
Aila Särkkä
Göteborgs universitet
Chalmers, Matematiska vetenskaper, Matematisk statistik
Claudia Redenbach
Technische Universität Kaiserslautern
Martina Sormani
Fraunhofer-Institut fur Techno- und Wirtschaftsmathematk
Technische Universität Kaiserslautern
Spatial Statistics
2211-6753 (ISSN)
Vol. 15 100-114Ämneskategorier
Matematik
Geologi
DOI
10.1016/j.spasta.2015.12.005