[aut, cre]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 2019) <doi:10.13140/RG.2.2.15437.18403>.
| Version: | 1.0.2 |
| Depends: | R (≥ 3.4.0) |
| Imports: | pracma, RANN |
| Suggests: | knitr, rmarkdown, OutliersO3, ggplot2, FNN |
| Published: | 2020-02-24 |
| 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_1.0.2.tar.gz |
| Windows binaries: | r-devel: dobin_1.0.2.zip, r-release: dobin_1.0.2.zip, r-oldrel: dobin_1.0.2.zip |
| macOS binaries: | r-release: dobin_1.0.2.tgz, r-oldrel: dobin_1.0.2.tgz |
| Old sources: | dobin archive |
| Reverse imports: | composits |
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