Design-based Spatial Inference
Design-Based Spatial Inference is a spatial inference methodology that belongs to the class of design-based approaches in spatial statistics, distinguished by its reliance on the sampling design as the foundation for valid inference about population parameters, rather than assuming a specific stochastic model for the spatial process.
17
Publications
1.3K
Citations
49
Authors
36
Institutions
Publications per year
2017–2026
7
Parents
17
Estimating the Encounter Rate Variance in Distance Sampling
Rachel M. Fewster, S. T. Buckland, Kenneth P. Burnham et al. · Biometrics · 2008 · 162 citations · Full text
1–5 of 17
49
SUNY College of Environmental Science and Forestry, United States
3 publications · 244 citations
3
h-index
2
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NOAA National Marine Fisheries Service Alaska Fisheries Science Center, United States
2 publications · 100 citations
2
h-index
1
h-index
1
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1–5 of 49
36
Environmental Protection Agency
Washington, United States
3 h-index
7 publications
440 citations
SUNY College of Environmental Science and Forestry
Syracuse, United States
3 h-index
3 publications
244 citations
University of Siena
Siena, Italy
2 h-index
5 publications
193 citations

Purchase College
Purchase, United States
2 h-index
2 publications
110 citations
NOAA National Marine Fisheries Service Alaska Fisheries Science Center
Seattle, United States
2 h-index
2 publications
189 citations

St. Lawrence University
Canton, United States
1 h-index
1 publications
27 citations
National Oceanic and Atmospheric Administration
Washington, United States
1 h-index
1 publications
27 citations
Institut de Veille Sanitaire
Saint-Maurice, France
1 h-index
3 publications
144 citations
1–8 of 36
3 publications · 244 citations
3
h-index
2 publications · 354 citations
2
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JSS · 1 publications · 73 citations
1
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1 publications · 26 citations
1
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1 publications · 27 citations
1
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1–5