Location and Scale Invariant Power Transformations
Assess normality of transformed data
Central normality test
Create transformation object skeleton
Empirical central normality test
Set transformation parameters
Compute residuals of transformation to normality
Huber M-estimate
Get lambda value
Set lambda value
Create Q-Q plot
Create residual plot
Transform values
power.transform: Transform Data to Normality using Power Transformatio...
Random Values from the Asymmetric Generalised Normal Distribution
Revert transformation
Get scale value
Set scale value
Get shift value
Set shift value
Box-Cox transformation object
Yeo-Johnson transformation object
Get transformation method
No transformation object
Generic transformation object
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.
Useful links