Bayesian Multivariate Forecasting

Bayesian Multivariate Forecasting is a statistical forecasting framework that integrates Bayesian inference with multivariate time series modeling to jointly predict multiple interdependent variables while quantifying uncertainty through posterior distributions.

32

Publications

2.7K

Citations

74

Authors

57

Institutions

Publications per year

2017–2026

14

Authors

74

  1. SR
    S. Rao Jammalamadaka

    University of California, Santa Barbara, United States

    3 publications · 92 citations

    3

    h-index

  2. NN
    Ning Ning

    University of California, Santa Barbara, United States

    3 publications · 92 citations

    3

    h-index

  3. JQ
    Jinwen Qiu

    University of California, Santa Barbara, United States

    3 publications · 92 citations

    3

    h-index

  4. MM
    Mac McKee

    Utah State University, United States

    2 publications · 56 citations

    2

    h-index

  5. TZ
    Tao Zha

    Federal Reserve Bank of Atlanta, United States

    2 publications · 1K citations

    2

    h-index

1–5 of 74

Venues

  1. Journal of Econometrics

    3 publications · 556 citations

    3

    h-index

  2. International Journal of Forecasting

    3 publications · 155 citations

    3

    h-index

  3. Journal of Statistical Planning and Inference

    1 publications · 10 citations

    1

    h-index

  4. Bulletin of the Seismological Society of America

    BSSA · 1 publications · 28 citations

    1

    h-index

  5. Mining Science and Technology (China)

    1 publications · 21 citations

    1

    h-index

1–5