Bayesian Hurdle Models

Bayesian Hurdle Models is a Bayesian statistical model for count data that combines a binary process modeling the presence or absence of events with a truncated count process for positive outcomes, thereby distinguishing between structural and sampling zeros through prior distributions on model parameters.

17

Publications

513

Citations

81

Authors

48

Institutions

Publications per year

2017–2026

11

Authors

81

  1. MS
    Md. Shafiur Rahman

    Hamamatsu University School of Medicine, Japan

    2 publications · 80 citations

    2

    h-index

  2. MG
    María Grazia Pennino

    Instituto Español de Oceanografía, Spain

    2 publications · 47 citations

    2

    h-index

  3. KT
    Khin Thet Swe

    The University of Tokyo, Japan

    2 publications · 80 citations

    2

    h-index

  4. MM
    Md Mizanur Rahman

    The University of Tokyo, Japan

    3 publications · 127 citations

    2

    h-index

  5. TE
    Tilman Eichstädt

    Coventry University, United Kingdom

    1 publications · 23 citations

    1

    h-index

1–5 of 81

Venues

  1. PLoS ONE

    3 publications · 105 citations

    3

    h-index

  2. Fisheries Oceanography

    1 publications · 18 citations

    1

    h-index

  3. Environmental and Ecological Statistics

    1 publications · 12 citations

    1

    h-index

  4. International Journal of Health Geographics

    1 publications · 37 citations

    1

    h-index

  5. BMC Infectious Diseases

    1 publications · 19 citations

    1

    h-index

1–5