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.