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1.2

Robust Multivariate Outlier Detection

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6.3Kdownloads / year
test coverage
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Overview

About
Maintained by Nathaniel E. HelwigFirst published 2025-05-301 releasesCRAN page ↗

Detection of multivariate outliers using robust estimates of location and scale. The Minimum Covariance Determinant (MCD) estimator is used to calculate robust estimates of the mean vector and covariance matrix. Outliers are determined based on robust Mahalanobis distances using either an unstructured covariance matrix, a principal components structured covariance matrix, or a factor analysis structured covariance matrix. Includes options for specifying the direction of interest for outlier detection for each variable.

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Health

CRAN checks
13OK
Slowest check: 55 s · r-oldrel-windows-x86_64
Code health
None
Tests · ratio 0.00
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Coverage
100%
Documentation · exports
1
Dependencies · direct
Check history
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
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Examples that run
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Documented parameters
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Return-value docs
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References docs
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Rank #7,661 · ~17/day · ~526/mo
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Dependencies

Declared dependencies
1 external dependency (excludes base and recommended)
Depends (2)
R >= 3.5.0robustbase
Imports (0)
none
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none
Suggests (0)
none
Enhances (0)
none
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Code & Tests

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People & History

People (3)
Maintainer (1)
Author, Maintainer
Authors (2)
Author, Maintainer
Contributors (1)
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Listed in earlier versions (3)
no longer listed · 1.2
no longer listed · 1.2
no longer listed · 1.2
Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.2Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-05-30
Total releases
1 / 1 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 3.5.0
Bundled data
25 KB / 1 file
Download size
38 KB
Installed size
not tracked yet
With dependencies
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