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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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.