Constrained Priors

Constrained Priors is a type of prior distribution in Bayesian statistics that incorporates explicit restrictions or limitations on the parameter space to reflect known structural constraints, physical boundaries, or logical dependencies, thereby distinguishing it from unconstrained priors by formally encoding domain-specific knowledge into the probabilistic model.

54

Publications

7.5K

Citations

146

Authors

117

Institutions

Publications per year

2017–2026

20

Authors

146

  1. MD
    Marco Del Negro

    Federal Reserve Bank of New York, United States

    3 publications · 417 citations

    3

    h-index

  2. RC
    Ronan Collobert

    Meta (Israel), Israel

    3 publications · 782 citations

    3

    h-index

  3. FS
    Frank Schorfheide

    University of Pennsylvania, United States

    3 publications · 417 citations

    3

    h-index

  4. IK
    Irene Klugkist

    Utrecht University, Netherlands

    2 publications · 136 citations

    2

    h-index

  5. LV
    Lindsay V. Clark

    University of Illinois Urbana-Champaign, United States

    2 publications · 132 citations

    2

    h-index

1–5 of 146

Venues

  1. Journal of Cosmology and Astroparticle Physics

    JCAP · 4 publications · 339 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 69 citations

    3

    h-index

  3. Biometrika

    2 publications · 374 citations

    2

    h-index

  4. 2

    h-index

  5. Bulletin of Mathematical Biology

    2 publications · 48 citations

    2

    h-index

1–5