Bayesian Threshold Estimation

Bayesian Threshold Estimation is a statistical method for inferring hearing thresholds that belongs to the class of Bayesian inference techniques and is distinguished by its incorporation of prior knowledge and probabilistic modeling to update threshold estimates based on observed behavioral responses.

67

Publications

3.1K

Citations

197

Authors

94

Institutions

Publications per year

2017–2026

12

Authors

197

  1. DG
    Daniel Gianola

    University of Wisconsin–Madison, United States

    4 publications · 443 citations

    4

    h-index

  2. JS
    Josef Schlittenlacher

    University of Cambridge, United Kingdom

    2 publications · 54 citations

    2

    h-index

  3. CF
    Catherine Forbes

    Monash University, Australia

    2 publications · 59 citations

    2

    h-index

  4. DS
    D. Sorensen

    University of Wisconsin–Madison, United States

    2 publications · 443 citations

    2

    h-index

  5. IR
    Inge Riis Korsgaard

    Aarhus University, Denmark

    2 publications · 398 citations

    2

    h-index

1–5 of 197

Venues

  1. Genetics Selection Evolution

    GSE · 7 publications · 675 citations

    7

    h-index

  2. Journal of Animal Science

    4 publications · 193 citations

    4

    h-index

  3. Journal of Dairy Science

    JDS · 3 publications · 137 citations

    3

    h-index

  4. Statistics in Medicine

    2 publications · 44 citations

    2

    h-index

  5. The Journal of the Acoustical Society of America

    JASA · 2 publications · 57 citations

    2

    h-index

1–5