Count Data Spatial Models
Count Data Spatial Models is a class of spatial econometric models that belong to the family of generalized linear models for count outcomes, distinguished by their explicit incorporation of spatial dependence structures—such as spatial lags, spatial errors, or spatial filtering components—to account for spatial autocorrelation in discrete non-negative integer-valued response variables.
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Publications
3.4K
Citations
201
Authors
135
Institutions
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2017–2026
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HIERARCHICAL SPATIAL MODELS OF ABUNDANCE AND OCCURRENCE FROM IMPERFECT SURVEY DATA
J. Andrew Royle, Marc Kéry, Roland Gautier et al. · Ecological Monographs · 2007 · 196 citations
Computing, Biostatistics, Ecology +17
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New South Wales Department of Primary Industries, Australia
2 publications · 48 citations
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1–5 of 201
135

University of British Columbia
Vancouver, Canada
4 h-index
7 publications
199 citations
United States Geological Survey
Reston, United States
3 h-index
6 publications
720 citations

University of Victoria
Victoria, Canada
3 h-index
5 publications
167 citations
North Carolina State University
Raleigh, United States
3 h-index
4 publications
86 citations
Upper Midwest Environmental Sciences Center
La Crosse, United States
2 h-index
4 publications
372 citations

University of Central Florida
Orlando, United States
2 h-index
2 publications
168 citations

South China University of Technology
Guangzhou, China
2 h-index
5 publications
126 citations
Tsinghua University
Beijing, China
2 h-index
2 publications
89 citations
1–8 of 135
JABES · 2 publications · 59 citations
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2 publications · 41 citations
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JRS · 2 publications · 138 citations
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2 publications · 190 citations
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2 publications · 33 citations
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