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Title:

Generalised least squares estimation of regularly varying space-time processes based on flexible observation schemes

Document type:
Zeitschriftenaufsatz
Author(s):
Buhl, S. and Klüppelberg, C.
Abstract:
Regularly varying stochastic processes model extreme dependence between process values at different locations and/or time points. For such stationary processes, we propose a two-step parameter estimation of the extremogram, when some part of the domain of interest is fixed and another increasing. We provide conditions for consistency and asymptotic normality of the empirical extremogram centred by a pre-asymptotic version for such observation schemes. For max-stable processes with Fréchet margin...     »
Keywords:
Brown-Resnick process, Extremogram, Generalised least squares estimation, Max-stable process, Observation schemes, Regularly varying process, Semiparametric estimation, Space-time process
Dewey Decimal Classification:
510 Mathematik
Journal title:
Extremes
Year:
2019
Journal volume:
22
Year / month:
2019-06
Quarter:
2. Quartal
Month:
Jun
Journal issue:
2
Pages contribution:
223-269
Language:
en
Fulltext / DOI:
doi:10.1007/s10687-018-0340-x
Publisher:
Springer Science and Business Media LLC
E-ISSN:
1386-19991572-915X
Notes:
published online: 03.01.2019
Date of publication:
01.06.2019
TUM Institution:
Lehrstuhl für Mathematische Statistik
Format:
Text
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