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Extreme Analysis of a Random Ordinary Differential Equation

Published online by Cambridge University Press:  30 January 2018

Jingchen Liu*
Affiliation:
Columbia University
Xiang Zhou*
Affiliation:
City University of Hong Kong
*
Postal address: Department of Statistics, Columbia University, 1255 Amsterdam Avenue, New York, NY 10027, USA. Email address: jcliu@stat.columbia.edu
∗∗ Postal address: Y6524 (Yellow Zone), 6/F Academic 1, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Hong Kong.
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Abstract

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In this paper we consider a one dimensional stochastic system described by an elliptic equation. A spatially varying random coefficient is introduced to account for uncertainty or imprecise measurements. We model the logarithm of this coefficient by a Gaussian process and provide asymptotic approximations of the tail probabilities of the derivative of the solution.

Type
Research Article
Copyright
© Applied Probability Trust 

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