Objective Bayesian Analysis

Objective Bayesian Analysis is a Bayesian inferential framework that belongs to the class of Bayesian methods and is distinguished by its use of objective, typically non-informative or reference priors intended to minimize subjective influence and ensure results are driven primarily by the observed data.

98

Publications

6.5K

Citations

149

Authors

114

Institutions

Publications per year

2017–2026

21

Variants

Objective Bayesian Inference

Authors

149

  1. YT
    Yincai Tang

    East China Normal University, China

    8 publications · 230 citations

    8

    h-index

  2. AX
    Ancha Xu

    East China Normal University, China

    7 publications · 228 citations

    7

    h-index

  3. JO
    James O. Berger

    Purdue University West Lafayette, United States

    6 publications · 1.8K citations

    6

    h-index

  4. DS
    Dongchu Sun

    University of Missouri, United States

    5 publications · 552 citations

    5

    h-index

  5. BL
    Brunero Liseo

    Sapienza University of Rome, Italy

    4 publications · 217 citations

    4

    h-index

1–5 of 149

Venues

  1. Bayesian Analysis

    10 publications · 1.1K citations

    10

    h-index

  2. Applied Mathematical Modelling

    5 publications · 167 citations

    5

    h-index

  3. Journal of Applied Econometrics

    5 publications · 628 citations

    5

    h-index

  4. Computational Statistics & Data Analysis

    CSDA · 3 publications · 64 citations

    3

    h-index

  5. 3

    h-index

1–5