Summary Statistics Selection

Summary Statistics Selection is the systematic process of identifying and choosing a subset of informative features or metrics from simulated data that optimally capture the relevant information for performing accurate and efficient inference in simulation-based models while minimizing dimensionality and preserving inferential validity.

96

Publications

7.6K

Citations

436

Authors

222

Institutions

Publications per year

2017–2026

30

Authors

436

  1. DP
    Dennis Prangle

    Newcastle University, United Kingdom

    3 publications · 685 citations

    3

    h-index

  2. JM
    John M. Connor

    Purdue University West Lafayette, United States

    3 publications · 60 citations

    3

    h-index

  3. PF
    Paul Fearnhead

    Lancaster University, United Kingdom

    2 publications · 660 citations

    2

    h-index

  4. MP
    Maarten Pieter Schinkel

    University of Amsterdam, Netherlands

    2 publications · 96 citations

    2

    h-index

  5. MC
    Martin Carree

    Maastricht University, Netherlands

    2 publications · 96 citations

    2

    h-index

1–5 of 436

Venues

  1. SSRN Electronic Journal

    Repository · 5 publications · 151 citations

    5

    h-index

  2. PLoS ONE

    5 publications · 298 citations

    5

    h-index

  3. Statistical Applications in Genetics and Molecular Biology

    SAGMB · 3 publications · 434 citations

    3

    h-index

  4. PubMed

    Repository · 3 publications · 125 citations

    3

    h-index

  5. Journal of Peace Research

    3 publications · 644 citations

    3

    h-index

1–5