Default Priors

Default Priors is a method in Bayesian statistics that specifies prior distributions automatically based on theoretical desiderata such as invariance, minimal informativeness, or reference properties, rather than on subjective or empirical information.

86

Publications

11.6K

Citations

196

Authors

132

Institutions

Publications per year

2017–2026

31

Authors

196

  1. QF
    Quentin F. Gronau

    University of Amsterdam, Netherlands

    4 publications · 247 citations

    4

    h-index

  2. JM
    Joris Mulder

    Tilburg University, Netherlands

    3 publications · 263 citations

    3

    h-index

  3. JO
    James O. Berger

    Purdue University West Lafayette, United States

    3 publications · 183 citations

    3

    h-index

  4. RE
    Robert E. Kass

    Carnegie Mellon University, United States

    3 publications · 1.5K citations

    3

    h-index

  5. BR
    Bruce Rannala

    University of California, Davis, United States

    3 publications · 232 citations

    3

    h-index

1–5 of 196

Venues

  1. 7

    h-index

  2. Bayesian Analysis

    5 publications · 777 citations

    5

    h-index

  3. arXiv (Cornell University)

    Repository · 4 publications · 156 citations

    4

    h-index

  4. Canadian Journal of Statistics

    CJS · 4 publications · 143 citations

    4

    h-index

  5. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 2 publications · 26 citations

    2

    h-index

1–5