Simulating mixture of sub-Gaussian spatial data

	Simulating mixture of sub-Gaussian spatial data
AUT Journal of Mathematics and Computing
مقاله 1، دوره 5، شماره 1، 2024، صفحه 1-9 اصل مقاله (912.02 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22060/ajmc.2023.22015.1130
نویسندگان
Seyedeh Somayeh Mousavi؛ Adel Mohammadpour^*
Department of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Iran
چکیده
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.
کلیدواژه‌ها
Simulation؛ Spatial data؛ Geostatistical data؛ SG$\alpha$S random field
مراجع

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