Bayesian Hazard Function Estimation

Bayesian Hazard Function Estimation is a statistical methodology that belongs to the class of Bayesian survival analysis techniques, distinguished by its use of prior distributions and posterior inference to estimate the time-varying hazard function while incorporating uncertainty and model parameters in a fully probabilistic framework.

136

Publications

4.5K

Citations

333

Authors

230

Institutions

Publications per year

2017–2026

34

Authors

333

  1. JA
    Jorge Alberto Achcar

    Universidade de São Paulo, Brazil

    5 publications · 99 citations

    5

    h-index

  2. DD
    David D. Hanagal

    Savitribai Phule Pune University, India

    5 publications · 72 citations

    5

    h-index

  3. MC
    Ming‐Hui Chen

    University of Connecticut, United States

    4 publications · 210 citations

    4

    h-index

  4. DK
    Dipak K. Dey

    University of Connecticut, United States

    4 publications · 121 citations

    4

    h-index

  5. JG
    Joseph G. Ibrahim

    University of North Carolina at Chapel Hill, United States

    3 publications · 164 citations

    3

    h-index

1–5 of 333

Venues

  1. Biometrics

    8 publications · 457 citations

    8

    h-index

  2. 8

    h-index

  3. Lifetime Data Analysis

    7 publications · 193 citations

    7

    h-index

  4. Computational Statistics & Data Analysis

    CSDA · 4 publications · 126 citations

    4

    h-index

  5. 4

    h-index

1–5