Outlier Identification

Outlier Identification is a methodological process in data analysis that distinguishes anomalous observations from normal data points based on their significant deviation from the underlying statistical or structural patterns of the dataset.

2.1K

Publications

172.1K

Citations

5.7K

Authors

2.1K

Institutions

Publications per year

2017–2026

663

Authors

5.7K

  1. PF
    Peter Filzmoser

    TU Wien, Austria

    14 publications · 1.4K citations

    13

    h-index

  2. AC
    Anthony C. Atkinson

    London School of Economics and Political Science, United Kingdom

    13 publications · 2.8K citations

    13

    h-index

  3. PJ
    Peter J. Rousseeuw

    University of Antwerp, Belgium

    11 publications · 9.1K citations

    11

    h-index

  4. DP
    Daniel Peña

    Universidad Carlos III de Madrid, Spain

    12 publications · 872 citations

    11

    h-index

  5. FA
    Fabrizio Angiulli

    University of Calabria, Italy

    11 publications · 1.1K citations

    11

    h-index

1–5 of 5.7K

Venues

  1. Technometrics

    79 publications · 18.3K citations

    40

    h-index

  2. Journal of the American Statistical Association

    50 publications · 8.7K citations

    35

    h-index

  3. Computational Statistics & Data Analysis

    CSDA · 30 publications · 3K citations

    25

    h-index

  4. Expert Systems with Applications

    24 publications · 1.1K citations

    18

    h-index

  5. Biometrika

    20 publications · 1.5K citations

    17

    h-index

1–5