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Is there some reasonable way to generate random data from a distribution that has some degree of skewness and/or kurtosis, but would otherwise be normal? thanks, -------------- next part -------------- A non-text attachment was scrubbed... Name: greiff.vcf Type: text/x-vcard Size: 398 bytes Desc: Card for Warren R. Greiff Url : https://stat.ethz.ch/pipermail/r-help/attachments/20011210/2170bc6f/greiff.vcf

Hello, The question looks like simple. It's probably even stupid. But I spent several hours searching Internet, downloaded tons of papers, where deviance is mentioned and... And haven't found an answer. Well, it is clear for me the using of entropy when I split some node of a classification tree. The sense is clear, because entropy is an old good measure of how uniform is distribution.