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The empirical central normality test is now dependent on the number of samples.
The test can now be called using ecn.test
. cn.test
is a stricter central
normality test whose test statistics are determined from strictly normal
distributions, instead of normal distributions with up to 10% outliers.
The robust location- and shift-invariant transformations now use weights optimised for achieving central normality.
This is the initial public release of the power.transform
package.
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