Bayesian Factor Models

Bayesian Factor Models is a statistical modeling framework within the class of factor models that incorporates Bayesian inference to estimate latent factors and model parameters, distinguishing itself by the use of prior distributions and posterior updating to account for uncertainty in factor structure and loading estimates.

198

Publications

12.9K

Citations

452

Authors

275

Institutions

Publications per year

2017–2026

51

Variants

Bayesian Factor Model

Authors

452

  1. DB
    David B. Dunson

    Duke University, United States

    5 publications · 613 citations

    5

    h-index

  2. SL
    Sik‐Yum Lee

    Chinese University of Hong Kong, Hong Kong SAR China

    5 publications · 248 citations

    5

    h-index

  3. GK
    Gary Koop

    University of Strathclyde, United Kingdom

    4 publications · 508 citations

    4

    h-index

  4. SK
    Sylvia Kaufmann

    National Bank of Austria, Austria

    4 publications · 106 citations

    4

    h-index

  5. MA
    M. Ayhan Köse

    Brookings Institution, United States

    4 publications · 1.6K citations

    4

    h-index

1–5 of 452

Venues

  1. SSRN Electronic Journal

    Repository · 20 publications · 774 citations

    14

    h-index

  2. Psychometrika

    9 publications · 468 citations

    9

    h-index

  3. arXiv (Cornell University)

    Repository · 6 publications · 178 citations

    6

    h-index

  4. Journal of Applied Econometrics

    5 publications · 596 citations

    5

    h-index

  5. BMC Bioinformatics

    4 publications · 162 citations

    4

    h-index

1–5