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

Authors

151

  1. SA
    Samuel A. Cushman

    Rocky Mountain Research (United States), United States

    2 publications · 247 citations

    2

    h-index

  2. RH
    Rolf Holderegger

    Swiss Federal Institute for Forest, Snow and Landscape Research, Switzerland

    2 publications · 80 citations

    2

    h-index

  3. SM
    Stéphanie Manel

    Centre National de la Recherche Scientifique, France

    1 publications · 38 citations

    1

    h-index

  4. CJ
    Christopher John Topping

    Aarhus University, Denmark

    1 publications · 67 citations

    1

    h-index

  5. DO
    David O. Wallin

    Western Washington University, United States

    1 publications · 161 citations

    1

    h-index

1–5 of 151

Venues

  1. Landscape Ecology

    4 publications · 602 citations

    4

    h-index

  2. Molecular Ecology Resources

    3 publications · 55 citations

    3

    h-index

  3. Heredity

    2 publications · 42 citations

    2

    h-index

  4. Journal of Theoretical Biology

    2 publications · 21 citations

    2

    h-index

  5. Physical Review Letters

    PRL · 1 publications · 48 citations

    1

    h-index

1–5