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:
power.transform_1.0.0.tar.gz
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power.transform.pdf |power.transform.html✨
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
Last updated 1 months agofrom:a2c584531a. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 22 2024 |
| R-4.5-win | OK | Nov 22 2024 |
| R-4.5-linux | OK | Nov 22 2024 |
| R-4.4-win | OK | Nov 22 2024 |
| R-4.4-mac | OK | Nov 22 2024 |
| R-4.3-win | OK | Nov 22 2024 |
| R-4.3-mac | OK | Nov 22 2024 |
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
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Assess normality of transformed data | assess_transformation |
| Create transformation object skeleton | create_transformer_skeleton |
| Set transformation parameters | find_transformation_parameters |
| Get lambda value | get_lambda get_lambda,transformationBoxCox-method get_lambda,transformationPowerTransform-method get_lambda,transformationYeoJohnson-method |
| Compute residuals of transformation to normality | get_residuals |
| Get scale value | get_scale get_scale,transformationBoxCox-method get_scale,transformationPowerTransform-method get_scale,transformationYeoJohnson-method |
| Get shift value | get_shift get_shift,transformationBoxCox-method get_shift,transformationPowerTransform-method get_shift,transformationYeoJohnson-method |
| Get transformation method | get_transformation_method get_transformation_method,transformationPowerTransform-method |
| Huber M-estimate | huber_estimate |
| Create Q-Q plot | plot_qq_plot |
| Create residual plot | plot_residual_plot |
| Transform values | power_transform |
| power.transform: Transform Data to Normality using Power Transformations | power.transform-package power.transform |
| Random Values from the Asymmetric Generalised Normal Distribution | ragn |
| Revert transformation | revert_power_transform |
| Set lambda value | set_lambda set_lambda,transformationBoxCox-method set_lambda,transformationPowerTransform-method set_lambda,transformationYeoJohnson-method |
| Set scale value | set_scale set_scale,transformationBoxCox-method set_scale,transformationPowerTransform-method set_scale,transformationYeoJohnson-method |
| Set shift value | set_shift set_shift,transformationBoxCox-method set_shift,transformationPowerTransform-method set_shift,transformationYeoJohnson-method |
| Box-Cox transformation object | transformationBoxCox-class transformationBoxCoxInvariant-class |
| No transformation object | transformationNone-class |
| Generic transformation object | transformationPowerTransform-class |
| Yeo-Johnson transformation object | transformationYeoJohnson-class transformationYeoJohnsonInvariant-class |
