Selection Function Modeling

Selection Function Modeling is a methodological framework in astrometric survey design that characterizes the observational biases and detection efficiencies of a survey by formally specifying the probability of selecting celestial sources based on their astrophysical and instrumental parameters.

26

Publications

1.4K

Citations

130

Authors

106

Institutions

Publications per year

2017–2026

12

Authors

130

  1. HR
    Hans‐Walter Rix

    Max Planck Institute for Astronomy, Germany

    3 publications · 364 citations

    3

    h-index

  2. AR
    Andrew R. Casey

    Monash University, Australia

    2 publications · 109 citations

    2

    h-index

  3. SK
    S. Khanna

    Max Planck Institute for Astronomy, Germany

    2 publications · 109 citations

    2

    h-index

  4. SO
    Semyeong Oh

    University of Cambridge, United Kingdom

    2 publications · 109 citations

    2

    h-index

  5. AC
    A. Castro-Ginard

    Universitat de Barcelona, Spain

    2 publications · 109 citations

    2

    h-index

1–5 of 130

Venues

  1. The Astrophysical Journal

    ApJ · 6 publications · 540 citations

    6

    h-index

  2. 5

    h-index

  3. Astronomy and Astrophysics

    4 publications · 151 citations

    3

    h-index

  4. Icarus

    2 publications · 58 citations

    2

    h-index

  5. Research in Astronomy and Astrophysics

    RAA · 1 publications · 36 citations

    1

    h-index

1–5