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power.transform

Location and Scale Invariant Power Transformations

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.

Versions across snapshots

VersionRepositoryFileSize
1.0.4 rolling linux/jammy R-4.5 power.transform_1.0.4.tar.gz 524.0 KiB
1.0.4 rolling linux/noble R-4.5 power.transform_1.0.4.tar.gz 523.8 KiB
1.0.4 rolling source/ R- power.transform_1.0.4.tar.gz 203.3 KiB
1.0.4 latest linux/jammy R-4.5 power.transform_1.0.4.tar.gz 524.0 KiB
1.0.4 latest linux/noble R-4.5 power.transform_1.0.4.tar.gz 523.8 KiB
1.0.4 latest source/ R- power.transform_1.0.4.tar.gz 203.3 KiB
1.0.4 2026-04-26 source/ R- power.transform_1.0.4.tar.gz 203.3 KiB
1.0.4 2026-04-23 source/ R- power.transform_1.0.4.tar.gz 203.3 KiB
1.0.4 2026-04-09 windows/windows R-4.5 power.transform_1.0.4.zip 527.8 KiB
1.0.1 2025-04-20 source/ R- power.transform_1.0.1.tar.gz 83.9 KiB

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