Cited by 2,982Advanced Statistical Methods and ModelsAnomaly Detection Techniques and ApplicationsStatistical Distribution Estimation and Applications

Identification of Outliers

Hawkins, D. M.·1980·Springer eBooks

Integrity signals

Registry

Crossref · 10.1007/978-94-015-3994-4

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Each specific anomaly detection model has its own definition of an anomaly, either explicitly or implicitly.

    “As this is informal, each specific anomaly detection model has its own definition of an anomaly, either explicitly or implicitly.”

    From A Survey on Explainable Anomaly Detection (2024) · cites this paper as [81]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Hawkins, D. M.
Affiliations
University of Minnesota (US)
Corresponding author
Hawkins, D. M.
Venue
Springer eBooks
Published
1980
OpenAlex
W2049058890
Cited by
2,982
References
3
Citations by year
2026: 76 · 2025: 152 · 2024: 136 · 2023: 151 · 2022: 182 · 2021: 181 · 2020: 175 · 2019: 180 · 2018: 152 · 2017: 144 · 2016: 124 · 2015: 129 · 2014: 143 · 2013: 108 · 2012: 96
FWCI
3.85
Type
book
Language
en
Open access
closed
Locations
  • Springer eBooks (publishedVersion)
  • CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
  • Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
Keywords
outlier detection, outliers, robust statistics

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review