Scale Priors

Scale Priors is a methodological construct in Bayesian statistics that specifies prior distributions on the scale parameters of a model to reflect uncertainty about the magnitude of variation while maintaining invariance under rescaling transformations.

20

Publications

1.6K

Citations

56

Authors

32

Institutions

Publications per year

2017–2026

6

Authors

56

  1. FJ
    Francisco J. Rubio

    University of Warwick, United Kingdom

    2 publications · 58 citations

    2

    h-index

  2. PR
    Paul R. Burton

    University of Leicester, United Kingdom

    1 publications · 516 citations

    1

    h-index

  3. MF
    Mark F. J. Steel

    University of Warwick, United Kingdom

    1 publications · 41 citations

    1

    h-index

  4. XF
    Xiaohan Fei

    University of California, Los Angeles, United States

    1 publications · 53 citations

    1

    h-index

  5. PS
    Patrisia Sherryl Santoso

    Industrial Technology Research Institute, Taiwan

    1 publications · 12 citations

    1

    h-index

1–5 of 56

Venues

  1. Bayesian Analysis

    2 publications · 501 citations

    2

    h-index

  2. Journal of Organizational Behavior

    OB · 1 publications · 10 citations

    1

    h-index

  3. Ecology

    1 publications · 48 citations

    1

    h-index

  4. 1

    h-index

  5. Statistics & Probability Letters

    1 publications · 17 citations

    1

    h-index

1–5