Probabilistic Population Synthesis

Probabilistic Population Synthesis is a synthetic population generation method that constructs individual-level demographic representations by statistically inferring the most likely distribution of attributes from aggregate data and marginal constraints using probabilistic modeling techniques.

10

Publications

673

Citations

24

Authors

24

Institutions

Publications per year

2017–2026

5

Authors

24

  1. BM
    Bernhard Müller

    Monash University, Australia

    2 publications · 192 citations

    2

    h-index

  2. IM
    Ilya Mandel

    University of Birmingham, United Kingdom

    2 publications · 192 citations

    2

    h-index

  3. JM
    John M. McPartland

    GW Pharmaceuticals (United Kingdom), United Kingdom

    1 publications · 64 citations

    1

    h-index

  4. LS
    Lijun Sun

    McGill University, Canada

    1 publications · 190 citations

    1

    h-index

  5. HT
    Harry Timmermans

    Eindhoven University of Technology, Netherlands

    1 publications · 79 citations

    1

    h-index

1–5 of 24

Venues

  1. 3

    h-index

  2. Vegetation History and Archaeobotany

    1 publications · 64 citations

    1

    h-index

  3. Astronomy and Astrophysics

    1 publications · 16 citations

    1

    h-index

  4. Repository for Publications and Research Data (ETH Zurich)

    Repository · 1 publications · 28 citations

    1

    h-index

  5. Regional Studies Regional Science

    RSRS · 1 publications · 18 citations

    1

    h-index

1–5