Title of article :
Simulating mixture of sub-Gaussian spatial data
Author/Authors :
Mousavi ، Somayeh Department of Mathematics and Computer Science - Amirkabir University of Technology (Tehran Polytechnic) , Mohammadpour ، Adel Department of Mathematics and Computer Science - Amirkabir University of Technology (Tehran Polytechnic)
Abstract :
Spatial datasets may contain extreme values and exhibit heavy tails. So, the Gaussianity assumption for the corresponding random field is not reasonable. A sub-Gaussian α-stable (SGαS) random field may be more suitable as a model for heavy-tailed spatial data. This paper focuses on geostatistical data and presents an algorithm for simulating SGαS random fields.
Keywords :
Simulation , Spatial Data , Geostatistical Data , SGαS Random field
Journal title :
AUT Journal of Mathematics and Computing
Journal title :
AUT Journal of Mathematics and Computing
