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:	1.0.3
Depends:	R (≥ 3.4.0)
Imports:	dbscan, ggplot2, pracma
Suggests:	knitr, rmarkdown, OutliersO3, FNN
Published:	2022-05-18
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

Documentation:

Reference manual:	dobin.pdf
Vignettes:	Introduction to dobin

Downloads:

Package source:	dobin_1.0.3.tar.gz
Windows binaries:	r-devel: dobin_1.0.3.zip, r-release: dobin_1.0.3.zip, r-oldrel: dobin_1.0.3.zip
macOS binaries:	r-release (arm64): dobin_1.0.3.tgz, r-oldrel (arm64): dobin_1.0.3.tgz, r-release (x86_64): dobin_1.0.3.tgz, r-oldrel (x86_64): dobin_1.0.3.tgz
Old sources:	dobin archive

Reverse dependencies:

Reverse imports:

composits

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