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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 |
DOI: | 10.32614/CRAN.package.dobin |
Author: | Sevvandi Kandanaarachchi [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 |
Reference manual: | dobin.pdf |
Vignettes: |
Introduction to dobin |
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 |
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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.