Survey Predictive Modeling
Survey Predictive Modeling is a computational or statistical methodology within historic resource survey that predicts the spatial distribution or likelihood of encountering cultural or historical resources by analyzing environmental, geographic, and socio-historical variables.
19
Publications
2.2K
Citations
35
Authors
31
Institutions
Publications per year
2017–2026
6
Parents
19
Fitting Regression Models to Survey Data
Thomas Lumley, Alastair Scott · Statistical Science · 2017 · 208 citations
Tree-based Machine Learning Methods for Survey Research
Christoph Kern, Thomas Klausch, Frauke Kreuter · PubMed · 2018 · 116 citations · Full text
1–5 of 19
35
University of California, Santa Barbara, United States
2 publications · 1.4K citations
2
h-index
2
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2
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2
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2
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1–5 of 35
31
University of Michigan
Ann Arbor, United States
3 h-index
7 publications
2.9K citations
United States Census Bureau
Suitland, United States
2 h-index
2 publications
22 citations

University of Auckland
Auckland, New Zealand
2 h-index
4 publications
538 citations
Hahnemann University Hospital
Philadelphia, United States
1 h-index
1 publications
25 citations
Korea National University of Education
Cheongju-si, South Korea
1 h-index
2 publications
22 citations

McGill University
Montreal, Canada
1 h-index
1 publications
11 citations
Inserm
Paris, France
1 h-index
6 publications
702 citations
University of California, Riverside
Riverside, United States
1 h-index
2 publications
48 citations
1–8 of 31
3 publications · 1.4K citations
3
h-index
2 publications · 41 citations
2
h-index
1 publications · 117 citations
1
h-index
1 publications · 18 citations
1
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1 publications · 33 citations
1
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1–5