Mixture Distribution Modeling

Mixture Distribution Modeling is a statistical modeling approach that represents the overall distribution of incubation periods as a weighted combination of distinct parametric distributions, each corresponding to a subpopulation or transmission pathway, thereby accounting for heterogeneity in disease progression dynamics.

392

Publications

23.8K

Citations

1K

Authors

530

Institutions

Publications per year

2017–2026

101

Authors

1K

  1. HW
    Henry W. Block

    University of Pittsburgh, United States

    5 publications · 143 citations

    5

    h-index

  2. AE
    Adrian E. Raftery

    University of Washington, United States

    5 publications · 822 citations

    5

    h-index

  3. TH
    Thomas H. Savits

    University of Pittsburgh, United States

    5 publications · 143 citations

    5

    h-index

  4. MV
    Matthias von Davier

    Educational Testing Service, United States

    5 publications · 172 citations

    5

    h-index

  5. AB
    André Berchtold

    University of Lausanne, Switzerland

    4 publications · 313 citations

    4

    h-index

1–5 of 1K

Venues

  1. Statistics in Medicine

    12 publications · 339 citations

    11

    h-index

  2. Biometrics

    10 publications · 2.4K citations

    10

    h-index

  3. arXiv (Cornell University)

    Repository · 9 publications · 291 citations

    9

    h-index

  4. Journal of the American Statistical Association

    8 publications · 3.8K citations

    8

    h-index

  5. Computational Statistics & Data Analysis

    CSDA · 7 publications · 191 citations

    7

    h-index

1–5