Functional Bayesian Inference

Functional Bayesian Inference is a statistical framework within functional time series analysis that extends Bayesian inference to infinite-dimensional functional data by specifying prior distributions over function spaces and updating them to posterior distributions conditioned on observed functional observations.

62

Publications

2.4K

Citations

160

Authors

115

Institutions

Publications per year

2017–2026

18

Authors

160

  1. FV
    Francesco Versace

    The University of Texas MD Anderson Cancer Center, United States

    3 publications · 170 citations

    3

    h-index

  2. DB
    David B. Dunson

    Duke University, United States

    3 publications · 106 citations

    3

    h-index

  3. JS
    Jeffrey S. Morris

    The University of Texas MD Anderson Cancer Center, United States

    3 publications · 157 citations

    3

    h-index

  4. MV
    Marina Vannucci

    Rice University, United States

    3 publications · 113 citations

    3

    h-index

  5. WP
    W.D. Penny

    University College London, United Kingdom

    3 publications · 388 citations

    3

    h-index

1–5 of 160

Venues

  1. NeuroImage

    10 publications · 683 citations

    10

    h-index

  2. 5

    h-index

  3. Bayesian Analysis

    4 publications · 230 citations

    4

    h-index

  4. The Annals of Applied Statistics

    AOAS · 3 publications · 159 citations

    3

    h-index

  5. Journal of Computational and Graphical Statistics

    JCGS · 3 publications · 100 citations

    3

    h-index

1–5