transformationPowerTransform-class

This is the superclass for transformation objects.

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.

Alex Zwanenburg

power.transform

Location and Scale Invariant Power Transformations

Steffen Löck

German Cancer Research Center (DKFZ) 

transformationPowerTransform-class function

<dl>
<dt><code>method</code></dt>
<dd>Main transformation method.</dd></dl>
<dt><code>complete</code></dt>
<dd>Indicates whether transformation parameters were set.</dd>
<dt><code>version</code></dt>
<dd>Version of the power.transform package that was used to create
the transformation objecst.</dd>

Slots

Generic transformation object — transformationPowerTransform-class

<dl>
<dt><code>method</code></dt>
<dd>Main transformation method.</dd>


<dt><code>complete</code></dt>
<dd>Indicates whether transformation parameters were set.</dd>


<dt><code>version</code></dt>
<dd>Version of the power.transform package that was used to create
the transformation objecst.</dd>


</dl>

transformationPowerTransform-class: Generic transformation object

Description

Arguments

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