Affiliation:
1. Columbia University
2. Royal Institute of Technology
3. University of Minnesota
Abstract
In this article, rare-event simulation for stochastic recurrence equations of the form
X
n
+1
=
A
n
+1
X
n
+
B
n
+1
,
X
0
=0
is studied, where {
A
n
;
n
≥ 1} and {
B
n
;
n
≥ 1} are independent sequences consisting of independent and identically distributed real-valued random variables. It is assumed that the tail of the distribution of
B
1
is regularly varying, whereas the distribution of
A
1
has a suitably light tail. The problem of efficient estimation, via simulation, of quantities such as
P
{
X
n
>b} and
P
{sup
k
≤
n
X
k
> b} for large
b
and
n
is studied. Importance sampling strategies are investigated that provide unbiased estimators with bounded relative error as
b
and
n
tend to infinity.
Funder
Division of Computer and Network Systems
Division of Civil, Mechanical and Manufacturing Innovation
Göran Gustafssons Stiftelse för Naturvetenskaplig och Medicinsk Forskning
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Science Applications,Modelling and Simulation
Cited by
1 articles.
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