Statistical Outlier Detection

Statistical Outlier Detection is a methodological framework within outlier detection that identifies anomalous observations by applying statistical models and significance tests to distinguish data points that deviate significantly from the assumed underlying distribution of the data.

1.7K

Publications

139.1K

Citations

3.8K

Authors

1.5K

Institutions

Publications per year

2017–2026

469

Authors

3.8K

  1. AC
    Anthony C. Atkinson

    London School of Economics and Political Science, United Kingdom

    20 publications · 3.3K citations

    18

    h-index

  2. PJ
    Peter J. Rousseeuw

    University of Antwerp, Belgium

    13 publications · 8.7K citations

    13

    h-index

  3. ŞH
    Şerif Hekimoğlu

    Yıldız Technical University, Türkiye

    12 publications · 310 citations

    12

    h-index

  4. MR
    Marco Riani

    University of Parma, Italy

    11 publications · 302 citations

    11

    h-index

  5. UG
    Ursula Gather

    TU Dortmund University, Germany

    10 publications · 1.2K citations

    10

    h-index

1–5 of 3.8K

Venues

  1. Technometrics

    81 publications · 17.7K citations

    39

    h-index

  2. Journal of the American Statistical Association

    64 publications · 8.5K citations

    39

    h-index

  3. Biometrika

    29 publications · 2.3K citations

    24

    h-index

  4. Computational Statistics & Data Analysis

    CSDA · 20 publications · 1.5K citations

    18

    h-index

  5. Journal of Computational and Graphical Statistics

    JCGS · 20 publications · 1.4K citations

    17

    h-index

1–5