Posterior Mean Estimation

Posterior Mean Estimation is a Bayesian inference method that belongs to the class of point estimation techniques, distinguished by its use of the expected value of the posterior distribution to estimate unknown parameters based on observed data and prior information.

349

Publications

24.6K

Citations

744

Authors

458

Institutions

Publications per year

2017–2026

69

Authors

744

  1. LV
    L. Varona

    Universidad de Zaragoza, Spain

    4 publications · 145 citations

    4

    h-index

  2. JO
    James O. Berger

    Purdue University West Lafayette, United States

    4 publications · 279 citations

    4

    h-index

  3. RK
    Robert Kohn

    UNSW Sydney, Australia

    4 publications · 177 citations

    4

    h-index

  4. TA
    Thomas A. Louis

    Johns Hopkins University, United States

    4 publications · 390 citations

    4

    h-index

  5. FZ
    Faker Zouaoui

    Sabre (United States), United States

    3 publications · 170 citations

    3

    h-index

1–5 of 744

Venues

  1. Journal of the American Statistical Association

    33 publications · 2.6K citations

    24

    h-index

  2. The Annals of Statistics

    15 publications · 2.4K citations

    14

    h-index

  3. arXiv (Cornell University)

    Repository · 12 publications · 283 citations

    11

    h-index

  4. 11

    h-index

  5. Biometrics

    7 publications · 468 citations

    7

    h-index

1–5