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Well known outlier detection techniques in the univariate case. Methods to deal with skewed distribution are included too. The Hidiroglou-Berthelot (1986) method to search for outliers in ratios of historical data is implemented as well. When available, survey weights can be used in outliers detection.
| Version: | 0.4 |
| Depends: | robustbase, Hmisc |
| Published: | 2022-05-31 |
| DOI: | 10.32614/CRAN.package.univOutl |
| Author: | Marcello D'Orazio |
| Maintainer: | Marcello D'Orazio <mdo.statmatch at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/marcellodo/univOutl |
| NeedsCompilation: | no |
| Materials: | NEWS |
| In views: | OfficialStatistics |
| CRAN checks: | univOutl results |
| Reference manual: | univOutl.pdf |
| Package source: | univOutl_0.4.tar.gz |
| Windows binaries: | r-devel: univOutl_0.4.zip, r-release: univOutl_0.4.zip, r-oldrel: univOutl_0.4.zip |
| macOS binaries: | r-release (arm64): univOutl_0.4.tgz, r-oldrel (arm64): univOutl_0.4.tgz, r-release (x86_64): univOutl_0.4.tgz, r-oldrel (x86_64): univOutl_0.4.tgz |
| Old sources: | univOutl archive |
| Reverse imports: | adamethods |
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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.