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Nov 20, 2017 at 0:27 comment added BigBendRegion Also, the given "definition" of heavier-tailed is actually quite silly. By that definition, the N(0,1) distribution is heavier-tailed than the .9999*U(-1,1) + .0001*U(-1000,1000) distribution. The latter distribution is extremely outlier-prone and has very high kurtosis, the former is not outlier-prone at all and has low kurtosis. The argument is a complete red herring, because it is not even a logical measure of "tailedness".
Nov 9, 2017 at 13:19 comment added BigBendRegion There is not just one measure of tails. E{Z^4*I(|Z| >1)} is one, E{Z^10 *I(|Z| > 5} another. For a sequence of distributions where kurtosis tends to infinity, E{Z^4 *I(|Z| > b)}/kurtosis -> 1, for any b; hence, large kurtosis is mostly determined by the tail. Further, the contribution of |Z| <1 to kurtosis is small, as noted below, for all distributions. Hence, kurtosis itself is a measure of tailweight, although not identical to other tailweight measures. Similarly, other tailweight measures do not measure the same thing as kurtosis. There are, after all, infinitely many tailweight measures.
Apr 13, 2017 at 12:44 history edited CommunityBot
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Sep 15, 2015 at 2:26 history edited Glen_b CC BY-SA 3.0
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Sep 15, 2015 at 2:15 history edited Glen_b CC BY-SA 3.0
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Sep 15, 2015 at 1:01 history answered Glen_b CC BY-SA 3.0