Assertion: distribution's tail | /r/HasProperty | heavy
Facets:
Source sentences:
text: Therefore, if an observed distribution has a kurtosis greater than three, the distribution is said to have heavy tails when compared to the normal distribution.
text: Often the ratio distributions are heavy-tailed, and it may be difficult to work with such distributions and develop an associated statistical test.
text: In many applications it is the right tail of the distribution that is of interest, but a distribution may have a heavy left tail, or both tails may be heavy.
text: In many applications it is the right tail of the distribution that is of interest, but a distribution may have a heavy left tail, or both tails may be heavy.
text: The tails of these distributions, to both the right and the left, are thick and heavy.
text: Except for the Gaussian which is a limiting case, all stable distributions have heavy tails and infinite variance.
text: All long-tailed distributions are heavy-tailed, but the converse is false, and it is possible to construct heavy-tailed distributions that are not long-tailed.
text: Since such a power is always bounded below by the probability density function of an exponential distribution, fat-tailed distributions are always heavy-tailed.