Geostatistical Random Fields
Geostatistical Random Fields is a spatial random field characterized by statistically interpolated spatial dependence structures, typically modeled through variograms or covariance functions to enable optimal prediction at unsampled locations.
89
Publications
5.4K
Citations
206
Authors
118
Institutions
Publications per year
2017–2026
28
Parents
89
On conditional and intrinsic autoregressions
Julian Besag, Charles Kooperberg · Biometrika · 1995 · 729 citations
Statistical Applications in the Spatial Sciences.
Gary C. White, Neil Wrigley · Biometrics · 1981 · 320 citations
Statistical Applications in the Spatial Sciences
Stanley V. Gregory, Neil Wrigley · Geographical Journal · 1982 · 229 citations
GSTools v1.3: a toolbox for geostatistical modelling in Python
Sebastian Müller, Lennart Schüler, Alraune Zech et al. · Geoscientific model development · 2022 · 212 citations · Full text
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118
Stanford University
Stanford, United States
6 h-index
9 publications
711 citations
University of Arizona
Tucson, United States
4 h-index
12 publications
260 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
4 h-index
13 publications
1.1K citations
Utrecht University
Utrecht, The Netherlands
3 h-index
3 publications
321 citations
Politecnico di Milano
Milan, Italy
3 h-index
7 publications
144 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
6 publications
168 citations
China University of Geosciences
Wuhan, China
2 h-index
7 publications
506 citations
Yangtze University
Jingzhou, China
2 h-index
4 publications
76 citations
1–8 of 118
9 publications · 281 citations
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CAGEO · 7 publications · 315 citations
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6 publications · 287 citations
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6 publications · 289 citations
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4 publications · 233 citations
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