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quickOutlier

0.1.5

Detect and Treat Outliers in Data Mining

0packages depend
1.5Kdownloads / year
68.8%test coverage
13/13checks pass

Overview

About
Maintained by Daniel López PérezFirst published 2025-12-192 releasesCRAN page ↗GitHub ↗

Implements a suite of tools for outlier detection and treatment in data mining. It includes univariate methods (Z-score, Interquartile Range), multivariate detection using Mahalanobis distance, and density-based detection (Local Outlier Factor) via the 'dbscan' package. It also provides functions for visualization using 'ggplot2' and data cleaning via Winsorization.

Install

Health

CRAN checks
13OK
Slowest check: 3.1 min · r-oldrel-macos-x86_64
Code health
Yes
Tests · ratio 0.27
68.8%
Coverage · measured lines
100%
Documentation · exports
5
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSYes · 67% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Downloads

1.5K
CRAN downloads in the past year
Rank #20,703 · ~4/day · ~125/mo
Daily download trend is not available in this view yet.
13730 days
53490 days
1.5K1 year
Compare downloads with other packages →
Also on58 r2u27 autocran

Repository

Repository
0Stars
0Forks
0Open issues
0Open PRs
1Releases
2Commits
1Contributors
2 commits · Last activity 2026-04-04

Repository practices

Upstream repositoryBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/daniellop1/quickoutlier on 2026-08-16.

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
7 external dependencies (excludes base and recommended)
Depends (0)
none
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (1)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Package Timeline

2 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.5Latest
    2026-02-13 · current release · diff ↗
  • 0.1.0
    2025-12-19
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-12-19
Total releases
2 / 1 yrs
License
MIT + file LICENSE OSI
Download size
1.2 MB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("quickOutlier")
López Pérez, D. (2026). quickOutlier: Detect and Treat Outliers in Data Mining (Version 0.1.5) [Computer software]. https://doi.org/10.32614/CRAN.package.quickOutlier

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for quickOutlier version 0.1.5 [Data set]. HJJB, LLC. Data release v2026-08-17. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-17, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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