Bayesian Time-varying Parameter Models

Bayesian Time-Varying Parameter Models is a statistical modeling framework within Bayesian time series analysis that characterizes dynamic systems by treating model parameters as stochastic processes evolving over time according to specified prior distributions and updating them sequentially via posterior inference.

87

Publications

5K

Citations

187

Authors

136

Institutions

Publications per year

2017–2026

31

Variants

Bayesian Tvp Models

Authors

187

  1. GK
    Gary Koop

    University of Strathclyde, United Kingdom

    6 publications · 287 citations

    6

    h-index

  2. LB
    Luca Benati

    European Central Bank, Germany

    4 publications · 228 citations

    4

    h-index

  3. MH
    Michael Halling

    TU Wien, Austria

    3 publications · 747 citations

    3

    h-index

  4. AR
    Alessandro Rebucci

    Johns Hopkins University, United States

    3 publications · 53 citations

    3

    h-index

  5. SF
    Sylvia Frühwirth‐Schnatter

    Vienna University of Economics and Business, Austria

    3 publications · 202 citations

    3

    h-index

1–5 of 187

Venues

  1. SSRN Electronic Journal

    Repository · 12 publications · 590 citations

    10

    h-index

  2. Journal of Econometrics

    7 publications · 702 citations

    7

    h-index

  3. Journal of Business and Economic Statistics

    JBES · 5 publications · 231 citations

    5

    h-index

  4. Applied Economics

    3 publications · 153 citations

    3

    h-index

  5. Computational Statistics & Data Analysis

    CSDA · 3 publications · 60 citations

    3

    h-index

1–5