Efficient simulation of finite horizon problems in queueing and insurance risk
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Publication:2465683
DOI10.1007/s11134-007-9050-9zbMath1145.90356OpenAlexW2103458848MaRDI QIDQ2465683
Leonardo Rojas-Nandayapa, Soren Asmussen
Publication date: 7 January 2008
Published in: Queueing Systems (Search for Journal in Brave)
Full work available at URL: https://pure.au.dk/ws/files/41916901/imf_thiele_2007_03.pdf
\(M/G/1\) queueComplexityLévy processBounded relative errorConditional Monte CarloFinite horizon ruin functionRegularly varying distribution
Cites Work
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- How large delays build up in a GI/G/1 queue
- Efficient rare-event simulation for the maximum of heavy-tailed random walks
- Importance sampling in the Monte Carlo study of sequential tests
- Heavy tail modeling and teletraffic data. (With discussions and rejoinder)
- Large deviations results for subexponential tails, with applications to insurance risk
- Rare events simulation for heavy-tailed distributions
- Ruin probabilities and overshoots for general Lévy insurance risk processes
- The probability of exceeding a high boundary on a random time interval for a heavy-tailed random walk
- Stochastic simulation: Algorithms and analysis
- On the efficiency of the Asmussen-Kroese-estimator and its application to stop-loss transforms
- Monte Carlo simulation and large deviations theory for uniformly recurrent Markov chains
- UNIFORM ESTIMATES FOR THE TAIL PROBABILITY OF MAXIMA OVER FINITE HORIZONS WITH SUBEXPONENTIAL TAILS
- Applied Probability and Queues
- Fast simulation of rare events in queueing and reliability models
- Improved algorithms for rare event simulation with heavy tails
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