Jeffreys Priors

Jeffreys Priors is a method of prior specification in Bayesian statistics that defines a non-informative prior distribution based on the square root of the determinant of the Fisher information matrix, ensuring invariance under reparameterization.

155

Publications

18.1K

Citations

258

Authors

159

Institutions

Publications per year

2017–2026

24

Authors

258

  1. SN
    Sa‐Aat Niwitpong

    King Mongkut's University of Technology North Bangkok, Thailand

    5 publications · 128 citations

    5

    h-index

  2. RE
    Robert E. Kass

    Carnegie Mellon University, United States

    4 publications · 1.7K citations

    4

    h-index

  3. JG
    Joseph G. Ibrahim

    University of North Carolina at Chapel Hill, United States

    4 publications · 245 citations

    4

    h-index

  4. KY
    Keying Ye

    Virginia Tech, United States

    4 publications · 77 citations

    4

    h-index

  5. NY
    Noppadon Yosboonruang

    King Mongkut's University of Technology North Bangkok, Thailand

    3 publications · 90 citations

    3

    h-index

1–5 of 258

Venues

  1. Journal of the American Statistical Association

    15 publications · 2.5K citations

    13

    h-index

  2. Biometrika

    10 publications · 5.4K citations

    10

    h-index

  3. The Annals of Statistics

    9 publications · 828 citations

    9

    h-index

  4. Statistical Science

    8 publications · 2.4K citations

    8

    h-index

  5. Bayesian Analysis

    5 publications · 149 citations

    5

    h-index

1–5