Gaussian Random Particles with Flexible Hausdorff Dimension. (June 2015)
- Record Type:
- Journal Article
- Title:
- Gaussian Random Particles with Flexible Hausdorff Dimension. (June 2015)
- Main Title:
- Gaussian Random Particles with Flexible Hausdorff Dimension
- Authors:
- Hansen, Linda V.
Thorarinsdottir, Thordis L.
Ovcharov, Evgeni
Gneiting, Tilmann
Richards, Donald - Abstract:
- Abstract : Gaussian particles provide a flexible framework for modelling and simulating three-dimensional star-shaped random sets. In our framework, the radial function of the particle arises from a kernel smoothing, and is associated with an isotropic random field on the sphere. If the kernel is a von Mises-Fisher density, or uniform on a spherical cap, the correlation function of the associated random field admits a closed form expression. The Hausdorff dimension of the surface of the Gaussian particle reflects the decay of the correlation function at the origin, as quantified by the fractal index. Under power kernels we obtain particles with boundaries of any Hausdorff dimension between 2 and 3.
- Is Part Of:
- Advances in applied probability. Volume 47:Number 2(2015)
- Journal:
- Advances in applied probability
- Issue:
- Volume 47:Number 2(2015)
- Issue Display:
- Volume 47, Issue 2 (2015)
- Year:
- 2015
- Volume:
- 47
- Issue:
- 2
- Issue Sort Value:
- 2015-0047-0002-0000
- Page Start:
- 307
- Page End:
- 327
- Publication Date:
- 2015-06
- Subjects:
- Celestial body, -- correlation function, -- fractal dimension, -- Lévy basis, -- random field on a sphere, -- simulation of star-shaped random set
60D05, -- 60G60, -- 37F35
Probabilities -- Periodicals
Stochastic models -- Periodicals
Electronic journals
Periodicals
519.2 - Journal URLs:
- http://www.appliedprobability.org/content.aspx?Group=journals&Page=apjournals ↗
- DOI:
- 10.1239/aap/1435236977 ↗
- Languages:
- English
- ISSNs:
- 0001-8678
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 8972.xml