The paper presents a method of computing the extremal index of a
real-valued, higher-order (kth-order, $k \geq 1$) stationary Markov
chain ${X_n}$. The method is based on the assumption that the joint
distribution of $k +1$ consecutive variables is in the domain of attraction of
some multivariate extreme value distribution. We introduce limiting
distributions of some rescaled stationary transition kernels, which are used to
define a new $k -1$th-order Markov chain ${Y_n}$, say. Then, the
kth-order Markov chain ${Z_n}$ defined by $Z_n = Y_1 + \dots + Y_n$ is
used to derive a representation for the extremal index of ${X_n}$. We further
establish convergence in distribution of multilevel exceedance point processes
for ${X_n}$ in terms of ${Z_n}$. The representations for the extremal index and
for quantities characterizing the distributional limits are well suited for
Monte Carlo simulation.
Publié le : 1998-05-14
Classification:
Extremal index,
multivariate extreme value distributions,
exceedance point processes,
stationary Markov chains,
60G70,
60J05,
60G10,
60G55
@article{1028903534,
author = {Yun, Seokhoon},
title = {The extremal index of a higher-order stationary Markov
chain},
journal = {Ann. Appl. Probab.},
volume = {8},
number = {1},
year = {1998},
pages = { 408-437},
language = {en},
url = {http://dml.mathdoc.fr/item/1028903534}
}
Yun, Seokhoon. The extremal index of a higher-order stationary Markov
chain. Ann. Appl. Probab., Tome 8 (1998) no. 1, pp. 408-437. http://gdmltest.u-ga.fr/item/1028903534/