Bayesian Smoothing Priors

Bayesian Smoothing Priors is a class of informative prior distributions in Bayesian categorical data analysis that incorporate regularization by shrinking extreme probability estimates toward more plausible values, thereby reducing overfitting and improving posterior stability in sparse data settings.

8

Publications

366

Citations

17

Authors

12

Institutions

Publications per year

2017–2026

0

Authors

17

  1. MS
    Marina Seikel

    University of Cape Town, South Africa

    2 publications · 45 citations

    2

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  2. CC
    Chris Clarkson

    University of Cape Town, South Africa

    2 publications · 45 citations

    2

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  3. AR
    Andrea Riebler

    Norwegian University of Science and Technology, Norway

    2 publications · 114 citations

    2

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  4. HR
    Håvard Rue

    Norwegian University of Science and Technology, Norway

    1 publications · 75 citations

    1

    h-index

  5. KK
    Koichi Katsura

    The Institute of Statistical Mathematics, Japan

    1 publications · 46 citations

    1

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1–5 of 17

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 45 citations

    2

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  2. Zurich Open Repository and Archive (University of Zurich)

    Repository · 1 publications · 75 citations

    1

    h-index

  3. Biometrika

    1 publications · 77 citations

    1

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  4. 1

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  5. 1

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1–5