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dobin: Dimension Reduction for Outlier Detection

A dimension reduction technique for outlier detection. DOBIN: a Distance based Outlier BasIs using Neighbours, constructs a set of basis vectors for outlier detection. This is not an outlier detection method; rather it is a pre-processing method for outlier detection. It brings outliers to the fore-front using fewer basis vectors (Kandanaarachchi, Hyndman 2020) <doi:10.1080/10618600.2020.1807353>.

Version: 1.0.4
Depends: R (≥ 3.4.0)
Imports: dbscan, ggplot2, pracma
Suggests: knitr, rmarkdown, OutliersO3, FNN
Published: 2022-08-25
Author: Sevvandi Kandanaarachchi ORCID iD [aut, cre]
Maintainer: Sevvandi Kandanaarachchi <sevvandik at gmail.com>
License: MIT + file LICENSE
URL: https://sevvandi.github.io/dobin/
NeedsCompilation: no
CRAN checks: dobin results

Documentation:

Reference manual: dobin.pdf
Vignettes: Introduction to dobin

Downloads:

Package source: dobin_1.0.4.tar.gz
Windows binaries: r-devel: dobin_1.0.4.zip, r-release: dobin_1.0.4.zip, r-oldrel: dobin_1.0.4.zip
macOS binaries: r-release (arm64): dobin_1.0.4.tgz, r-oldrel (arm64): dobin_1.0.4.tgz, r-release (x86_64): dobin_1.0.4.tgz, r-oldrel (x86_64): dobin_1.0.4.tgz
Old sources: dobin archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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