Sensitivity Analysis In Bayesian Models

Sensitivity Analysis in Bayesian Models is a methodological framework within Bayesian statistics that systematically evaluates the robustness of posterior inferences to variations in prior specifications, likelihood assumptions, or model structure.

169

Publications

11.4K

Citations

369

Authors

233

Institutions

Publications per year

2017–2026

32

Authors

369

  1. PG
    Paul Gustafson

    University of British Columbia, Canada

    10 publications · 439 citations

    10

    h-index

  2. KW
    Keith Worden

    University of Sheffield, United Kingdom

    6 publications · 148 citations

    6

    h-index

  3. LC
    Lawrence C. McCandless

    Simon Fraser University, Canada

    5 publications · 288 citations

    5

    h-index

  4. WB
    W. Becker

    University of Sheffield, United Kingdom

    5 publications · 135 citations

    5

    h-index

  5. JR
    Jennifer Rowson

    University of Sheffield, United Kingdom

    4 publications · 113 citations

    4

    h-index

1–5 of 369

Venues

  1. Journal of the American Statistical Association

    12 publications · 613 citations

    11

    h-index

  2. Mechanical Systems and Signal Processing

    MSSP · 7 publications · 262 citations

    7

    h-index

  3. Statistics in Medicine

    5 publications · 336 citations

    5

    h-index

  4. Reliability Engineering & System Safety

    4 publications · 652 citations

    4

    h-index

  5. arXiv (Cornell University)

    Repository · 4 publications · 204 citations

    4

    h-index

1–5