Bayesian Severity Modeling

Bayesian Severity Modeling is a statistical modeling framework within claims severity analysis that employs Bayesian inference to estimate and update the probability distribution of claim amounts by incorporating prior knowledge and observed data.

11

Publications

1.1K

Citations

24

Authors

25

Institutions

Publications per year

2017–2026

2

Authors

24

  1. KM
    Kara M. Kockelman

    The University of Texas at Austin, United States

    3 publications · 645 citations

    3

    h-index

  2. JM
    Jianming Ma

    Texas Department of Transportation, United States

    3 publications · 645 citations

    3

    h-index

  3. MM
    Mohammad Mehdi Sepehri

    Tarbiat Modares University, Iran

    1 publications · 39 citations

    1

    h-index

  4. GW
    Gareth W. Peters

    University College London, United Kingdom

    1 publications · 33 citations

    1

    h-index

  5. JV
    Jéssika Viviani Okumura

    Universidade Estadual Paulista (Unesp), Brazil

    1 publications · 32 citations

    1

    h-index

1–5 of 24

Venues

  1. Accident Analysis & Prevention

    2 publications · 524 citations

    2

    h-index

  2. 2

    h-index

  3. 1

    h-index

  4. SSRN Electronic Journal

    Repository · 1 publications · 33 citations

    1

    h-index

  5. Decision Support Systems

    1 publications · 41 citations

    1

    h-index

1–5