Simulation analytics for virtual statistics via K nearest neighbors

Yujing Lin, Barry L. Nelson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

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 languageEnglish (US)
Title of host publication2016 Winter Simulation Conference
Subtitle of host publicationSimulating Complex Service Systems, WSC 2016
EditorsTheresa M. Roeder, Peter I. Frazier, Robert Szechtman, Enlu Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages448-459
Number of pages12
ISBN (Electronic)9781509044863
DOIs
StatePublished - Jul 2 2016
Event2016 Winter Simulation Conference, WSC 2016 - Arlington, United States
Duration: Dec 11 2016Dec 14 2016

Publication series

NameProceedings - Winter Simulation Conference
Volume0
ISSN (Print)0891-7736

Other

Other2016 Winter Simulation Conference, WSC 2016
CountryUnited States
CityArlington
Period12/11/1612/14/16

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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  • Cite this

    Lin, Y., & Nelson, B. L. (2016). Simulation analytics for virtual statistics via K nearest neighbors. In T. M. Roeder, P. I. Frazier, R. Szechtman, & E. Zhou (Eds.), 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016 (pp. 448-459). [7822111] (Proceedings - Winter Simulation Conference; Vol. 0). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2016.7822111