… modeling. Chapter 6 gives the dimensionless treatment of regular variation and its probabilistic
… discuss why it is difficult to bootstrap heavy-tail phenomena. Chapter 7 exploits the weak …

… This paper empirically investigates the asymptotic behaviour of the flood probability
distribution and more precisely the possible occurrence of heavy tail distributions, generally …

… , the moment estimator discerns a light tail more effectively than the Hill estimator, and thus
it is often useful to apply the moment estimator to see if y < O, which would rule out heavy tail …

… This tutorial has discussed statistical models for analyzing long-range dependence and
impulsive phenomena that appear in high-speed network traffic. The main challenge of this …

… an archetype for understanding and modeling phenomena that span multiple scales. In
pursuing this objective, should one pursue detailed neurophysiological models for each scale-…

… , SGD exhibits a ‘heavy-tail phenomenon’, meaning that the law of the iterates converges to
a heavy-tailed distribution. We rigorously prove that, this phenomenon is not specific to deep …

… Just like the popular Hill estimator in the continuous heavy-tail situation, the estimator ̂β
we propose can be derived by means of a suitable reformulation of the regularly varying …

… loss data, statistical investigation quite often indicates random variables with an heavy tail.
As described in the introductory part (Chapter 1) of the book, many events in the stock market …

… a versatile hydrologic probability model with three parameters. The proposed model is a …
From this, it is evident the distribution reflects light and heavy tail behavior. Moreover, it is …

… We show that some heavy-tail phenomena observed in large deviations can be explained
by the same mechanism as for the Wiener chaoses, meaning that the deviations are created, …