Package: quickOutlier
Title: Detect and Treat Outliers in Data Mining
Version: 0.1.0
Authors@R: 
    person("Daniel", "López Pérez", email = "dlopez350@icloud.com", role = c("aut", "cre"))
Description: 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.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: dbscan, ggplot2, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
URL: https://github.com/daniellop1/quickOutlier
BugReports: https://github.com/daniellop1/quickOutlier/issues
NeedsCompilation: no
Packaged: 2025-12-15 12:16:19 UTC; dlopez
Author: Daniel López Pérez [aut, cre]
Maintainer: Daniel López Pérez <dlopez350@icloud.com>
Repository: CRAN
Date/Publication: 2025-12-19 15:00:02 UTC
Built: R 4.5.2; ; 2025-12-21 22:54:46 UTC; unix
