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Document type:
Zeitschriftenaufsatz 
Author(s):
Buhl, S. and Klüppelberg, C. 
Title:
Generalised least squares estimation of regularly varying space-time processes based on flexible observation schemes 
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:
Pages contribution:
223-269 
Language:
en 
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