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Estimating geometric anisotropy in spatial point patterns

Tuomas Rajala (Institutionen för matematiska vetenskaper, matematisk statistik) ; Aila Särkkä (Institutionen för matematiska vetenskaper, matematisk statistik) ; C. Redenbach ; M. Sormani
Spatial Statistics (2211-6753). Vol. 15 (2016), p. 100-114.
[Artikel, refereegranskad vetenskaplig]

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.

Nyckelord: Spatial point process, Anisotropy, Non-parametric statistics, Ellipsoid, Polar ice



Denna post skapades 2016-04-29. Senast ändrad 2016-10-26.
CPL Pubid: 235595

 

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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)

Ämnesområden

Matematik
Geologi

Chalmers infrastruktur