Abstract Details
Activity Number:
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635
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 7, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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IMS
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Abstract #312490
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View Presentation
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Title:
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Max-Stable Processes on River Networks
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Author(s):
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Sebastian Engelke*+ and Peiman Asadi and Anthony Davison
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Companies:
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Université de Lausanne/École Polytechnique Fédérale de Lausanne and Université de Lausanne and EPFL
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Keywords:
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Extreme Value Theory ;
Max-stable Process ;
Extreme Value Statistics
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Abstract:
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Max-stable processes are suitable models for extreme events that exhibit spatial dependencies. The dependence measure is usually a function of Euclidean distance between two locations. In this talk, we model extreme river discharges on a river network in the upper Danube catchment, where flooding regularly causes huge damage. Dependence is more complex in this case as it goes along the river flow. For non-extreme data a Gaussian moving average model on stream networks was proposed by Ver Hoef and Peterson (2010, J. Amer. Statist. Assoc.). Inspired by their work, we introduce a max-stable process on the river network that allows flexible modeling of flood events and that enables risk assessment even at locations without a gauging station. Recent methods from extreme value statistics are used to fit this process to a big data set from the Danube area.
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Authors who are presenting talks have a * after their name.
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