Bayesian Statistics

Bayesian Statistics is a branch of statistical inference that interprets probability as a measure of belief or confidence in an event, updating prior beliefs with observed data through Bayes' theorem to yield posterior probabilities.

32.5K

Publications

2.7M

Citations

51K

Authors

8.2K

Institutions

Publications per year

2017–2026

8K

Authors

51K

  1. DB
    David B. Dunson

    Duke University, United States

    153 publications · 10.4K citations

    58

    h-index

  2. EW
    Eric‐Jan Wagenmakers

    University of Amsterdam, Netherlands

    111 publications · 15.1K citations

    53

    h-index

  3. AG
    Andrew Gelman

    Columbia University, United States

    83 publications · 52.1K citations

    51

    h-index

  4. MI
    Michael I. Jordan

    University of California, Berkeley, United States

    78 publications · 16.3K citations

    49

    h-index

  5. AE
    Adrian E. Raftery

    University of Washington, United States

    72 publications · 38.8K citations

    47

    h-index

1–5 of 51K

Venues

  1. Journal of the American Statistical Association

    1.1K publications · 210.3K citations

    196

    h-index

  2. 120

    h-index

  3. The Annals of Statistics

    421 publications · 66K citations

    109

    h-index

  4. Biometrika

    423 publications · 67.6K citations

    106

    h-index

  5. arXiv (Cornell University)

    Repository · 1.2K publications · 71.1K citations

    106

    h-index

1–5