Multivariate Statistical Fingerprinting

Multivariate Statistical Fingerprinting is a statistical method that distinguishes sediment sources by identifying unique geochemical or physical signatures through the simultaneous analysis of multiple variables within a multivariate dataset.

65

Publications

3.1K

Citations

380

Authors

151

Institutions

Publications per year

2017–2026

27

Authors

380

  1. AL
    Adrian L. Collins

    Rothamsted Research, United Kingdom

    2 publications · 105 citations

    2

    h-index

  2. JK
    Jeremy K. Nicholson

    Imperial College London, United Kingdom

    2 publications · 68 citations

    2

    h-index

  3. PF
    Peter Filzmoser

    TU Wien, Austria

    2 publications · 85 citations

    2

    h-index

  4. LW
    Larry W. Lake

    The University of Texas at Austin, United States

    2 publications · 31 citations

    2

    h-index

  5. EE
    E. Escobar

    The University of Texas at Austin, United States

    2 publications · 31 citations

    2

    h-index

1–5 of 380

Venues

  1. Journal of Agricultural and Food Chemistry

    6 publications · 377 citations

    6

    h-index

  2. 4

    h-index

  3. Journal of Separation Science

    5 publications · 69 citations

    4

    h-index

  4. Analytical Chemistry

    3 publications · 286 citations

    3

    h-index

  5. Frontiers in Pharmacology

    2 publications · 85 citations

    2

    h-index

1–5