Bayesian Gamma Regression

Bayesian Gamma Regression is a Bayesian generalized linear model that specifies the gamma distribution as the response distribution and uses Bayesian inference for parameter estimation, distinguishing it by incorporating prior distributions over the regression coefficients and modeling positive, continuous, right-skewed outcomes through a log-link function.

6

Publications

160

Citations

28

Authors

21

Institutions

Publications per year

2017–2026

3

Authors

28

  1. HL
    Hao Lyu

    Washington State University, United States

    1 publications · 35 citations

    1

    h-index

  2. MD
    Mahesh D. Pandey

    University of Waterloo, Canada

    1 publications · 36 citations

    1

    h-index

  3. SS
    Santos Sánchez‐Cambronero

    University of Castilla-La Mancha, Spain

    1 publications · 26 citations

    1

    h-index

  4. QC
    Qingxia Chen

    Vanderbilt University, United States

    1 publications · 28 citations

    1

    h-index

  5. ZP
    Zhiying Pan

    Amgen (United States), United States

    1 publications · 28 citations

    1

    h-index

1–5 of 28

Venues

  1. PLoS ONE

    2 publications · 35 citations

    2

    h-index

  2. Computers & Operations Research

    1 publications · 26 citations

    1

    h-index

  3. Accident Analysis & Prevention

    1 publications · 35 citations

    1

    h-index

  4. Lifetime Data Analysis

    1 publications · 28 citations

    1

    h-index

  5. Reliability Engineering & System Safety

    1 publications · 36 citations

    1

    h-index

1–5