Package: power.transform 1.0.0

Alex Zwanenburg

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.

Authors:Alex Zwanenburg [aut, cre], Steffen Löck [aut], German Cancer Research Center [cph]

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NEWS

Peer review:

Bug tracker:https://github.com/oncoray/power.transform/issues

On CRAN:

17 exports 1.70 score 3 dependencies 1 scripts 42 downloads

Last updated 5 hours agofrom:e9126ac268. Checks:OK: 7. Indexed: yes.

Exports:assess_transformationcreate_transformer_skeletonfind_transformation_parametersget_lambdaget_residualsget_scaleget_shiftget_transformation_methodhuber_estimateplot_qq_plotplot_residual_plotpower_transformragnrevert_power_transformset_lambdaset_scaleset_shift

Dependencies:data.tablenloptrrlang