Species Sampling Models

Species Sampling Models is a class of Bayesian nonparametric probability models that generate exchangeable random partitions of data by assigning observations to latent categories interpreted as "species," distinguished by their use of random discrete probability measures—such as the Dirichlet process—to model the unknown number and frequencies of these categories.

43

Publications

4.3K

Citations

125

Authors

89

Institutions

Publications per year

2017–2026

11

Authors

125

  1. SF
    Stefano Favaro

    University of Turin, Italy

    3 publications · 76 citations

    3

    h-index

  2. DR
    Duccio Rocchini

    Fondazione Edmund Mach, Italy

    3 publications · 78 citations

    3

    h-index

  3. TS
    Tsung‐Jen Shen

    National Chung Hsing University, Taiwan

    3 publications · 298 citations

    3

    h-index

  4. AG
    Antoine Guisan

    University of Lausanne, Switzerland

    2 publications · 615 citations

    2

    h-index

  5. AZ
    Alexander Zizka

    University of Gothenburg, Sweden

    2 publications · 140 citations

    2

    h-index

1–5 of 125

Venues

  1. Ecography

    3 publications · 513 citations

    3

    h-index

  2. Methods in Ecology and Evolution

    3 publications · 61 citations

    2

    h-index

  3. The Annals of Applied Probability

    2 publications · 52 citations

    2

    h-index

  4. Conservation Biology

    2 publications · 1.3K citations

    2

    h-index

  5. Ecology

    2 publications · 205 citations

    2

    h-index

1–5