Posterior Calibration

Posterior Calibration is a statistical framework that ensures the empirical coverage rates of Bayesian posterior credible intervals match their nominal levels under repeated sampling, thereby aligning the Bayesian posterior distribution with frequentist calibration standards.

33

Publications

2.5K

Citations

62

Authors

51

Institutions

Publications per year

2017–2026

10

Authors

62

  1. PB
    Paul‐Christian Bürkner

    University of Stuttgart, Germany

    2 publications · 47 citations

    2

    h-index

  2. NH
    Niko Huurre

    Massachusetts Institute of Technology, United States

    2 publications · 47 citations

    2

    h-index

  3. AV
    Aki Vehtari

    Aalto University, Finland

    2 publications · 47 citations

    2

    h-index

  4. NS
    Nicholas Syring

    North Carolina State University, United States

    2 publications · 108 citations

    2

    h-index

  5. MM
    Martin Modrák

    Czech Academy of Sciences, Czechia

    2 publications · 47 citations

    2

    h-index

1–5 of 62

Venues

  1. Bayesian Analysis

    4 publications · 163 citations

    4

    h-index

  2. The American Statistician

    3 publications · 1.1K citations

    3

    h-index

  3. 3

    h-index

  4. Test

    2 publications · 30 citations

    2

    h-index

  5. arXiv (Cornell University)

    Repository · 2 publications · 26 citations

    2

    h-index

1–5