Abstract
The threshold bootstrap (TB) is a promising new method of inference for a single autocorrelatcd data series, such as the output of a discrete event simulation. The method works by resampling runs of data created when the series crosses a threshold level, such as the series mean. We performed a Monte Carlo evaluation of the TB using three types of data: white noise, first-order autoregressive, and delays in an M/M/1 queue. The results show that the TB produces accurate and tight estimates of the standard deviation of the sample mean and valid confidence intervals.
Original language | English (US) |
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Title of host publication | Proceedings of the 25th Conference on Winter Simulation, WSC 1993 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 498-502 |
Number of pages | 5 |
Volume | Part F129590 |
ISBN (Electronic) | 078031381X |
DOIs | |
State | Published - Dec 1 1993 |
Externally published | Yes |
Event | 25th Conference on Winter Simulation, WSC 1993 - Los Angeles, United States Duration: Dec 12 1993 → Dec 15 1993 |
Other
Other | 25th Conference on Winter Simulation, WSC 1993 |
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Country/Territory | United States |
City | Los Angeles |
Period | 12/12/93 → 12/15/93 |
ASJC Scopus subject areas
- Software
- Modeling and Simulation
- Computer Science Applications