Title :
Finite sample behaviour of the mixed moment estimator in dependent frameworks
Author :
Gomes, M. Ivette ; Miranda, M. Cristina
Author_Institution :
DEIO, Univ. de Lisboa, Lisbon, Portugal
Abstract :
In this paper, via Monte Carlo techniques and for dependent structures, like the max-autoregressive processes and the m-dependent processes, we explore the behavior of a recently introduced extreme value index estimator, the mixed moment estimator. The dependent stationary sequences considered provide a wide spectrum of dependency, with an extremal index ranging from a value close to one (as happens in identicallly distributed settings, where exceedances of high thresholds appear isolated) to any value smaller than one, a situation in which exceedances of high levels appear in clusters of a mean size approximately equal to the reciprocal of that extremal index.
Keywords :
Monte Carlo methods; autoregressive processes; estimation theory; Monte Carlo technique; dependent frameworks; dependent stationary sequences; extreme value index estimator; finite sample behaviour; independent process; max-autoregressive process; mixed moment estimator; Delta modulation; Distribution functions; Information technology; Monte Carlo methods; Probability distribution; Statistical analysis; Statistical distributions; Statistics; Tail; Zinc; Monte Carlo simulation; Statistics of extremes; dependent models; heavy tails; mixed moment estimator; semi-parametric estimation;
Conference_Titel :
Information Technology Interfaces, 2009. ITI '09. Proceedings of the ITI 2009 31st International Conference on
Conference_Location :
Dubrovnik
Print_ISBN :
978-953-7138-15-8
DOI :
10.1109/ITI.2009.5196086