Efficient simulation of finite horizon problems in queueing and insurance risk

Rojas-Nandayapa, L and Asmussen, S (2007) Efficient simulation of finite horizon problems in queueing and insurance risk. Queueing Systems, 57 2-3: 85-97. doi:10.1007/s11134-007-9050-9


Author Rojas-Nandayapa, L
Asmussen, S
Title Efficient simulation of finite horizon problems in queueing and insurance risk
Journal name Queueing Systems   Check publisher's open access policy
ISSN 0257-0130
1572-9443
Publication date 2007-11
Sub-type Article (original research)
DOI 10.1007/s11134-007-9050-9
Volume 57
Issue 2-3
Start page 85
End page 97
Total pages 13
Place of publication New York, U.S.A.
Publisher Springer New York LLC
Language eng
Formatted abstract
Let ψ(u,t) be the probability that the workload in an initially empty M/G/1 queue exceeds u at time t<∞, or, equivalently, the ruin probability in the classical Crámer-Lundberg model. Assuming service times/claim sizes to be subexponential, various Monte Carlo estimators for ψ(u,t) are suggested. A key idea behind the estimators is conditional Monte Carlo. Variance estimates are derived in the regularly varying case, the efficiencies are compared numerically and also the estimators are shown to have bounded relative error in some main cases. In part, also extensions to general Lévy processes are treated.
Keyword Bounded relative error
Complexity
Conditional Monte Carlo
Lévy process
Regularly varying distribution
Finite horizon ruin function
M/G/1 queue
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Mathematics and Physics
 
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Created: Thu, 02 Dec 2010, 12:33:18 EST by Dr Leonardo Rojas-nandayapa on behalf of Mathematics