Simulation and Estimation of Extreme Quantiles and Extreme Probabilities

Let X be a random vector with distribution μ on ℝ d and Φ be a mapping from ℝ d to ℝ. That mapping acts as a black box, e.g., the result from some computer experiments for which no analytical expression is available. This paper presents an efficient algorithm to estimate a tail probability given a q...

Full description

Saved in:
Bibliographic Details
Published in:Applied mathematics & optimization Vol. 64; no. 2; pp. 171 - 196
Main Authors: Guyader, Arnaud, Hengartner, Nicolas, Matzner-Løber, Eric
Format: Journal Article
Language:English
Published: New York Springer-Verlag 01.10.2011
Springer Nature B.V
Springer Verlag (Germany)
Subjects:
ISSN:0095-4616, 1432-0606
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Let X be a random vector with distribution μ on ℝ d and Φ be a mapping from ℝ d to ℝ. That mapping acts as a black box, e.g., the result from some computer experiments for which no analytical expression is available. This paper presents an efficient algorithm to estimate a tail probability given a quantile or a quantile given a tail probability. The algorithm improves upon existing multilevel splitting methods and can be analyzed using Poisson process tools that lead to exact description of the distribution of the estimated probabilities and quantiles. The performance of the algorithm is demonstrated in a problem related to digital watermarking.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-2
content type line 23
ISSN:0095-4616
1432-0606
DOI:10.1007/s00245-011-9135-z