Location- and scale-invariant Box-Cox and Yeo-Johnson power transformations allow for transforming variables with distributions distant from 0 to normality. Transformers are implemented as S4 objects. These allow for transforming new instances to normality after optimising fitting parameters on other data. A test for central normality allows for rejecting transformations that fail to produce a suitably normal distribution, independent of sample number.
| Version: | 1.0.1 |
| Depends: | R (≥ 3.5) |
| Imports: | data.table, methods, rlang (≥ 1.0.0), nloptr |
| Suggests: | ggplot2 (≥ 3.4.0), testthat (≥ 3.0.0) |
| Published: | 2025-04-12 |
| DOI: | 10.32614/CRAN.package.power.transform |
| Author: | Alex Zwanenburg |
| Maintainer: | Alex Zwanenburg <alexander.zwanenburg at nct-dresden.de> |
| BugReports: | https://github.com/oncoray/power.transform/issues |
| License: | EUPL version 1.1 | EUPL version 1.2 [expanded from: EUPL] |
| URL: | https://github.com/oncoray/power.transform |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | power.transform results |
| Reference manual: | power.transform.html , power.transform.pdf |
| Package source: | power.transform_1.0.1.tar.gz |
| Windows binaries: | r-devel: power.transform_1.0.1.zip, r-release: power.transform_1.0.1.zip, r-oldrel: power.transform_1.0.1.zip |
| macOS binaries: | r-release (arm64): power.transform_1.0.1.tgz, r-oldrel (arm64): power.transform_1.0.1.tgz, r-release (x86_64): power.transform_1.0.1.tgz, r-oldrel (x86_64): power.transform_1.0.1.tgz |
| Old sources: | power.transform archive |
| Reverse suggests: | familiar |
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