Contamination Models

Contamination Models is a statistical framework that belongs to the class of outlier handling methods, distinguished by its assumption that observed data arise from a mixture of a primary distribution of interest and one or more contaminating distributions that generate outliers.

117

Publications

5.4K

Citations

303

Authors

185

Institutions

Publications per year

2017–2026

29

Authors

303

  1. AP
    Antonio Punzo

    University of Catania, Italy

    4 publications · 114 citations

    4

    h-index

  2. CG
    Chao Gao

    University of Chicago, United States

    3 publications · 167 citations

    3

    h-index

  3. PD
    Paul D. McNicholas

    University of Guelph, Canada

    3 publications · 70 citations

    3

    h-index

  4. VJ
    Vı́ctor J. Yohai

    Universidad de Buenos Aires, Argentina

    3 publications · 555 citations

    3

    h-index

  5. TK
    Takafumi Kanamori

    Nagoya University, Japan

    2 publications · 85 citations

    2

    h-index

1–5 of 303

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 135 citations

    7

    h-index

  2. Bernoulli

    4 publications · 140 citations

    4

    h-index

  3. The Annals of Statistics

    4 publications · 590 citations

    4

    h-index

  4. 4

    h-index

  5. 3

    h-index

1–5