Document Type : Original Article

**Authors**

Department of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Iran

**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 $\alpha$-stable (SG$\alpha$S) 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 SG$\alpha$S random fields.

**Keywords**

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January 2024

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