2008
DOI: 10.1016/j.spl.2007.11.025
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How to compute the extremal index of stationary random fields

Abstract: We present local dependence conditions for stationary random fields under which the extremal index and the asymptotic distribution of the maximum M (n 1 ,...,n d ) can be calculated from the joint distribution of a finite number s 1 s 2 of variables.keywords: Extremal index, local and long range dependence, random field.

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Cited by 24 publications
(13 citation statements)
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“…Let the assumptions of the theorem be satisfied. Then (8) holds. Dividing the set {M p(n) > v n } into p * (n) = p 1 (n)p 2 (n) · · · p d (n) disjoint sets and applying monotonicity and stationarity we obtain that…”
Section: Main Theoremmentioning
confidence: 96%
“…Let the assumptions of the theorem be satisfied. Then (8) holds. Dividing the set {M p(n) > v n } into p * (n) = p 1 (n)p 2 (n) · · · p d (n) disjoint sets and applying monotonicity and stationarity we obtain that…”
Section: Main Theoremmentioning
confidence: 96%
“…So it is rather surprising that there seems to be no existing limit theory for m-dependent stationary random fields. To the authors' knowledge the only attempts in this direction have been made by Turkman (2006) and Ferreira and Pereira (2008), but their results do not yield any concise method of calculating the limits and the extremal index for m-dependent random fields. In particular, the formula proposed in the latter paper does not work for the simple 1-dependent random field given in Example 5.5 below.…”
Section: Introductionmentioning
confidence: 98%
“…then θ is called the extremal index. To the computation of the extremal index of a random field in N 2 , the paper [13] is devoted; in [14], the asymptotic location of the maximum of a random field with a certain extremal index was studied.…”
Section: Introductionmentioning
confidence: 99%