Exact sampling of the infinite horizon maximum of a random walk over a nonlinear boundary
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AbstractWe present the first algorithm that samples maxn≥0{Sn − nα}, where Sn is a mean zero random walk, and nα with $\alpha \in ({1 \over 2},1)$ defines a nonlinear boundary. We show that our algorithm has finite expected running time. We also apply this algorithm to construct the first exact simulation method for the steady-state departure process of a GI/GI/∞ queue where the service time distribution has infinite mean.
2006 ◽
Vol 51
(3)
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pp. 519-525
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1999 ◽
Vol 36
(03)
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pp. 934-940
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