Extremal clustering under moderate long range dependence and moderately heavy tails
Chen, Zaoli; Samorodnitsky, Gennady
We study clustering of the extremes in a stationary sequence with subexponential tails in the maximum domain of attraction of the Gumbel We obtain functional limit theorems in the space of random sup- measures and in the space D(0, ∞). The limits have the Gumbel distribu- tion if the memory is only moderately long. However, as our results demon- strate rather strikingly, the “heuristic of a single big jump” could fail even in a moderately long range dependence setting. As the tails become lighter, the extremal behavior of a stationary process may depend on multiple large values of the driving noise.
extreme value theory; long range dependence; random sup-measure; stable regenerative set; subexponential tails; extremal clustering; Gumbel domain of attraction