Tail asymptotics for the supremum of an infinitely divisible field with convolution equivalent Lévy measure
Research output: Contribution to journal › Journal article › Research › peer-review
Standard
Tail asymptotics for the supremum of an infinitely divisible field with convolution equivalent Lévy measure. / Rønn-Nielsen, Anders; Jensen, Eva B. Vedel.
In: Journal of Applied Probability, Vol. 53, No. 1, 2016, p. 244-261.Research output: Contribution to journal › Journal article › Research › peer-review
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - JOUR
T1 - Tail asymptotics for the supremum of an infinitely divisible field with convolution equivalent Lévy measure
AU - Rønn-Nielsen, Anders
AU - Jensen, Eva B. Vedel
PY - 2016
Y1 - 2016
N2 - We consider a continuous, infinitely divisible random field in Rd given as an integral of a kernel function with respect to a Lévy basis with convolution equivalent Lévy measure. For a large class of such random fields we compute the asymptotic probability that the supremum of the field exceeds the level x as x → ∞. Our main result is that the asymptotic probability is equivalent to the right tail of the underlying Lévy measure.
AB - We consider a continuous, infinitely divisible random field in Rd given as an integral of a kernel function with respect to a Lévy basis with convolution equivalent Lévy measure. For a large class of such random fields we compute the asymptotic probability that the supremum of the field exceeds the level x as x → ∞. Our main result is that the asymptotic probability is equivalent to the right tail of the underlying Lévy measure.
U2 - 10.1017/jpr.2015.22
DO - 10.1017/jpr.2015.22
M3 - Journal article
VL - 53
SP - 244-261.
JO - Journal of Applied Probability
JF - Journal of Applied Probability
SN - 0021-9002
IS - 1
ER -
ID: 137321051