HRTnomaly

cranv25.11.22

Historical, Relational, and Tail Anomaly-Detection Algorithms. The presence of outliers in a dataset can substantially bias the results of statistical analyses. To correct for outliers, micro edits are manually performed on all records. A set of constraints and decision rules is typically used to aid the editing process. However, straightforward decision rules

License AGPL-3network copyleft0 versions1 maintainers3 deps59 weekly dl
https://CRAN.R-project.org/package=HRTnomaly
42
/ 100
Health
safe to use

[email protected] is safe to use (health: 42/100)

Health breakdown0 – 100
15/25
maintenance
0/20
popularity
25/25
security
0/15
maturity
2/15
community
Vulnerabilities
0
none known

Health History

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Dependencies (3)
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First published · 2025-11-25 11:53:06

Last updated · 2025-11-25T10:32:22+00:00

HRTnomaly — Health Score 42/100 | DepScope