Statistical Landscape Modeling
Statistical Landscape Modeling is a computational framework that belongs to the class of fitness landscape analysis methods, distinguished by its use of statistical inference techniques to approximate and interpret the structure of genotypic or phenotypic fitness landscapes from empirical data.
37
Publications
2.4K
Citations
151
Authors
109
Institutions
Publications per year
2017–2026
11
Parents
37
1–5 of 37
151
Rocky Mountain Research (United States), United States
2 publications · 247 citations
2
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Swiss Federal Institute for Forest, Snow and Landscape Research, Switzerland
2 publications · 80 citations
2
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1
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1
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1
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1–5 of 151
109
Colorado State University
Fort Collins, United States
4 h-index
6 publications
164 citations

Northern Arizona University
Flagstaff, United States
3 h-index
4 publications
781 citations
University of Tennessee at Knoxville
Knoxville, United States
3 h-index
5 publications
158 citations
ETH Zurich
Zurich, Switzerland
2 h-index
4 publications
147 citations
Rocky Mountain Research (United States)
Salt Lake City, United States
2 h-index
3 publications
408 citations

Utah State University
Logan, United States
2 h-index
2 publications
128 citations
Rocky Mountain Research Station
Fort Collins, United States
2 h-index
3 publications
408 citations

Santa Fe Institute
Santa Fe, United States
2 h-index
2 publications
184 citations
1–8 of 109
4 publications · 602 citations
4
h-index
3 publications · 55 citations
3
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2 publications · 42 citations
2
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2 publications · 21 citations
2
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PRL · 1 publications · 48 citations
1
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