Package: power.transform 1.0.4

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]

power.transform_1.0.4.tar.gz
power.transform_1.0.4.zip(r-4.7)power.transform_1.0.4.zip(r-4.6)power.transform_1.0.4.zip(r-4.5)
power.transform_1.0.4.tgz(r-4.6-any)power.transform_1.0.4.tgz(r-4.5-any)
power.transform_1.0.4.tar.gz(r-4.7-any)power.transform_1.0.4.tar.gz(r-4.6-any)
power.transform_1.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
power.transform/json (API)
NEWS

# Install 'power.transform' in R:
install.packages('power.transform', repos = c('https://oncoray.r-universe.dev', 'https://cloud.r-project.org'))

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

On CRAN:

Conda:

data-preprocessingstatistics

3.18 score 2 scripts 140 downloads 18 exports 3 dependencies

Last updated from:4449577708. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK147
source / vignettesOK193
linux-release-x86_64OK147
macos-release-arm64OK97
macos-oldrel-arm64OK123
windows-develOK115
windows-releaseOK125
windows-oldrelOK111
wasm-releaseOK98

Exports:assess_transformationcreate_transformer_skeletonecn_testfind_transformation_parametersget_lambdaget_residualsget_scaleget_shiftget_transformation_methodhuber_estimateplot_qq_plotplot_residual_plotpower_transformragnrevert_power_transformset_lambdaset_scaleset_shift

Dependencies:data.tablenloptrrlang

Readme and manuals

Help Manual

Help pageTopics
Assess normality of transformed dataassess_transformation
Create transformation object skeletoncreate_transformer_skeleton
Empirical central normality testecn_test
Set transformation parametersfind_transformation_parameters
Get lambda valueget_lambda get_lambda,transformationBoxCox-method get_lambda,transformationPowerTransform-method get_lambda,transformationYeoJohnson-method
Compute residuals of transformation to normalityget_residuals
Get scale valueget_scale get_scale,transformationBoxCox-method get_scale,transformationPowerTransform-method get_scale,transformationYeoJohnson-method
Get shift valueget_shift get_shift,transformationBoxCox-method get_shift,transformationPowerTransform-method get_shift,transformationYeoJohnson-method
Get transformation methodget_transformation_method get_transformation_method,transformationPowerTransform-method
Huber M-estimatehuber_estimate
Create Q-Q plotplot_qq_plot
Create residual plotplot_residual_plot
Transform valuespower_transform
power.transform: Transform Data to Normality using Power Transformationspower.transform-package power.transform
Random Values from the Asymmetric Generalised Normal Distributionragn
Revert transformationrevert_power_transform
Set lambda valueset_lambda set_lambda,transformationBoxCox-method set_lambda,transformationPowerTransform-method set_lambda,transformationYeoJohnson-method
Set scale valueset_scale set_scale,transformationBoxCox-method set_scale,transformationPowerTransform-method set_scale,transformationYeoJohnson-method
Set shift valueset_shift set_shift,transformationBoxCox-method set_shift,transformationPowerTransform-method set_shift,transformationYeoJohnson-method
Box-Cox transformation objecttransformationBoxCox-class transformationBoxCoxInvariant-class
No transformation objecttransformationNone-class
Generic transformation objecttransformationPowerTransform-class
Yeo-Johnson transformation objecttransformationYeoJohnson-class transformationYeoJohnsonInvariant-class