Compositional Data Analysis

Compositional Data Analysis is a statistical methodology that addresses the analysis of data representing parts of a whole, where the relative proportions among components are mathematically constrained to sum to a constant, thereby requiring specialized techniques to account for their intrinsic interdependence and avoid spurious correlations arising from this compositional structure.

1.6K

Publications

99.3K

Citations

5.7K

Authors

1.9K

Institutions

Publications per year

2017–2026

559

Variants

Coda

Authors

5.7K

  1. KH
    Karel Hron

    Palacký University Olomouc, Czechia

    38 publications · 4.5K citations

    27

    h-index

  2. JA
    Josep Antoni Martín Fernández

    Universitat de Girona, Spain

    34 publications · 3.1K citations

    24

    h-index

  3. PF
    Peter Filzmoser

    TU Wien, Austria

    29 publications · 3K citations

    22

    h-index

  4. JA
    J. Aitchison

    University of Glasgow, United Kingdom

    24 publications · 9.8K citations

    22

    h-index

  5. VP
    Vera Pawlowsky‐Glahn

    Universitat de Girona, Spain

    25 publications · 2.2K citations

    19

    h-index

1–5 of 5.7K

Venues

  1. Journal of Geochemical Exploration

    21 publications · 841 citations

    20

    h-index

  2. Journal of Agricultural and Food Chemistry

    23 publications · 1.6K citations

    18

    h-index

  3. Mathematical Geology

    16 publications · 2.1K citations

    18

    h-index

  4. PLoS ONE

    21 publications · 2.2K citations

    17

    h-index

  5. Mathematical Geosciences

    21 publications · 1.8K citations

    16

    h-index

1–5