Predictive Model Averaging

Predictive Model Averaging is a Bayesian model averaging technique that belongs to the class of ensemble prediction methods, distinguished by its formal integration of posterior model probabilities to weight predictions across a set of candidate models, thereby accounting for model uncertainty in inferential and predictive tasks.

39

Publications

2.4K

Citations

88

Authors

72

Institutions

Publications per year

2017–2026

17

Authors

88

  1. XZ
    Xinyu Zhang

    Chinese Academy of Sciences, China

    6 publications · 427 citations

    6

    h-index

  2. JL
    Jialiang Li

    National University of Singapore, Singapore

    2 publications · 85 citations

    2

    h-index

  3. SW
    Shouyang Wang

    Chinese Academy of Sciences, China

    2 publications · 75 citations

    2

    h-index

  4. PC
    Paola Cinnella

    Arts et Métiers, France

    2 publications · 133 citations

    2

    h-index

  5. FF
    Fang Fang

    University of Michigan, United States

    2 publications · 84 citations

    2

    h-index

1–5 of 88

Venues

  1. Journal of Econometrics

    4 publications · 374 citations

    4

    h-index

  2. International Journal of Forecasting

    3 publications · 149 citations

    3

    h-index

  3. SSRN Electronic Journal

    Repository · 3 publications · 87 citations

    3

    h-index

  4. Economics Letters

    2 publications · 75 citations

    2

    h-index

  5. Bayesian Analysis

    2 publications · 516 citations

    2

    h-index

1–5