Multimodal Distribution Analysis

Multimodal Distribution Analysis is a statistical methodology that identifies and interprets multiple distinct modes or peaks within a distribution, distinguishing itself from unimodal analysis by explicitly modeling complex data structures arising from heterogeneous underlying processes or subpopulations.

135

Publications

9.6K

Citations

394

Authors

213

Institutions

Publications per year

2017–2026

36

Authors

394

  1. LC
    Loren Cobb

    Medical University of South Carolina, United States

    3 publications · 422 citations

    3

    h-index

  2. PK
    Peter Koppstein

    Washington University in St. Louis, United States

    2 publications · 262 citations

    2

    h-index

  3. DJ
    Daniel J. Henderson

    Binghamton University, United States

    2 publications · 109 citations

    2

    h-index

  4. JA
    Jose Ameijeiras‐Alonso

    Universidade de Santiago de Compostela, Spain

    2 publications · 131 citations

    2

    h-index

  5. HT
    Hidetaka Tobita

    University of Fukui, Japan

    2 publications · 59 citations

    2

    h-index

1–5 of 394

Venues

  1. 6

    h-index

  2. PLoS ONE

    3 publications · 63 citations

    3

    h-index

  3. 3

    h-index

  4. Journal of Data Science

    2 publications · 37 citations

    2

    h-index

  5. Journal of the American Ceramic Society

    2 publications · 59 citations

    2

    h-index

1–5