TY - JOUR
T1 - Extreme analysis of a random ordinary differential equation
AU - LIU, Jingchen
AU - ZHOU, Xiang
PY - 2014/12
Y1 - 2014/12
N2 - 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.
AB - 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.
KW - Extremes
KW - Random differential equation
KW - Rare event
UR - http://www.scopus.com/inward/record.url?scp=84922388986&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84922388986&origin=recordpage
U2 - 10.1239/jap/1421763325
DO - 10.1239/jap/1421763325
M3 - RGC 21 - Publication in refereed journal
SN - 0021-9002
VL - 51
SP - 1021
EP - 1036
JO - Journal of Applied Probability
JF - Journal of Applied Probability
IS - 4
ER -