Abstract
Virtual statistics are performance measures that are conditional on the occurrence of an event; virtual waiting time of a customer arriving to a queue at time t is one example. In this paper, we describe a k-nearest-neighbor method for estimating virtual statistics post-simulation from the retained sample paths, examining both its small-sample and asymptotic properties. We implement leave-one-replication-out cross validation for tuning the parameter k, and compare the prediction performance of the k-nearest-neighbor estimator with a time-bucket estimator.
Original language | English (US) |
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Title of host publication | 2016 Winter Simulation Conference |
Subtitle of host publication | Simulating Complex Service Systems, WSC 2016 |
Editors | Theresa M. Roeder, Peter I. Frazier, Robert Szechtman, Enlu Zhou |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 448-459 |
Number of pages | 12 |
ISBN (Electronic) | 9781509044863 |
DOIs | |
State | Published - Jul 2 2016 |
Event | 2016 Winter Simulation Conference, WSC 2016 - Arlington, United States Duration: Dec 11 2016 → Dec 14 2016 |
Publication series
Name | Proceedings - Winter Simulation Conference |
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Volume | 0 |
ISSN (Print) | 0891-7736 |
Other
Other | 2016 Winter Simulation Conference, WSC 2016 |
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Country/Territory | United States |
City | Arlington |
Period | 12/11/16 → 12/14/16 |
Funding
This research was partially supported by the National Science Foundation under Grant Number CMMI- 1537060 and GOALI co-sponsor SAS Institute.
ASJC Scopus subject areas
- Software
- Modeling and Simulation
- Computer Science Applications