Decision-theoretic Model Averaging

Decision-Theoretic Model Averaging is a Bayesian model averaging framework that formalizes model uncertainty quantification and parameter estimation within a decision-theoretic paradigm by optimally combining posterior model predictions according to a specified loss function and prior beliefs.

21

Publications

1.3K

Citations

60

Authors

52

Institutions

Publications per year

2017–2026

9

Authors

60

  1. CS
    Christoph Schleicher

    Bank of England, United Kingdom

    1 publications · 81 citations

    1

    h-index

  2. MH
    M. Hashem Pesaran

    University of Southern California, United States

    1 publications · 81 citations

    1

    h-index

  3. GT
    Geoffrey T. Fong

    University of Waterloo, Canada

    1 publications · 112 citations

    1

    h-index

  4. WT
    W. Todd Maddox

    Arizona State University, United States

    1 publications · 98 citations

    1

    h-index

  5. TT
    Terence Tai‐Leung Chong

    Chinese University of Hong Kong, Hong Kong SAR China

    1 publications · 35 citations

    1

    h-index

1–5 of 60

Venues

  1. 1

    h-index

  2. Acta Psychologica

    1 publications · 79 citations

    1

    h-index

  3. 1

    h-index

  4. American Economic Review

    1 publications · 22 citations

    1

    h-index

  5. IRIS Research product catalog (Sapienza University of Rome)

    Repository · 1 publications · 81 citations

    1

    h-index

1–5