Bayesian Cluster Detection

Bayesian Cluster Detection is a probabilistic method for identifying spatially or temporally localized aggregations of events by incorporating prior distributions and updating beliefs through Bayesian inference to distinguish true clusters from random variation.

61

Publications

4.1K

Citations

255

Authors

159

Institutions

Publications per year

2017–2026

9

Authors

255

  1. BA
    B. Ascaso

    Instituto de Astrofísica de Andalucía, Spain

    5 publications · 107 citations

    5

    h-index

  2. NB
    N. Benı́tez

    Instituto de Astrofísica de Andalucía, Spain

    4 publications · 90 citations

    4

    h-index

  3. AJ
    A. J. Cenarro

    Centro de Estudios de Física del Cosmos de Aragón, Spain

    2 publications · 42 citations

    2

    h-index

  4. AM
    A. Molino

    Instituto de Astrofísica de Andalucía, Spain

    2 publications · 42 citations

    2

    h-index

  5. MK
    Murray K. Clayton

    University of Wisconsin–Madison, United States

    2 publications · 96 citations

    2

    h-index

1–5 of 255

Venues

  1. 6

    h-index

  2. Biometrics

    3 publications · 400 citations

    3

    h-index

  3. Genetics

    3 publications · 847 citations

    3

    h-index

  4. Journal of Neuroscience Methods

    2 publications · 86 citations

    2

    h-index

  5. Statistics in Medicine

    2 publications · 96 citations

    2

    h-index

1–5