Simulation analytics for virtual statistics via K nearest neighbors

Yujing Lin; Barry L. Nelson

doi:10.1109/WSC.2016.7822111

Simulation analytics for virtual statistics via K nearest neighbors

Yujing Lin, Barry L. Nelson

Industrial Engineering and Management Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 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 language	English (US)
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	https://doi.org/10.1109/WSC.2016.7822111
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
Volume	0
ISSN (Print)	0891-7736

Other

Other	2016 Winter Simulation Conference, WSC 2016
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

Access to Document

10.1109/WSC.2016.7822111

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). Article 7822111 (Proceedings - Winter Simulation Conference; Vol. 0). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2016.7822111

Lin, Yujing ; Nelson, Barry L. / Simulation analytics for virtual statistics via K nearest neighbors. 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016. editor / Theresa M. Roeder ; Peter I. Frazier ; Robert Szechtman ; Enlu Zhou. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 448-459 (Proceedings - Winter Simulation Conference).

@inproceedings{af680b3f6b3f4c7a996e7a68f0861b76,

title = "Simulation analytics for virtual statistics via K nearest neighbors",

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.",

author = "Yujing Lin and Nelson, \{Barry L.\}",

year = "2016",

month = jul,

day = "2",

doi = "10.1109/WSC.2016.7822111",

language = "English (US)",

series = "Proceedings - Winter Simulation Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "448--459",

editor = "Roeder, \{Theresa M.\} and Frazier, \{Peter I.\} and Robert Szechtman and Enlu Zhou",

booktitle = "2016 Winter Simulation Conference",

address = "United States",

note = "2016 Winter Simulation Conference, WSC 2016 ; Conference date: 11-12-2016 Through 14-12-2016",

}

Lin, Y & Nelson, BL 2016, Simulation analytics for virtual statistics via K nearest neighbors. in TM Roeder, PI Frazier, R Szechtman & E Zhou (eds), 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016., 7822111, Proceedings - Winter Simulation Conference, vol. 0, Institute of Electrical and Electronics Engineers Inc., pp. 448-459, 2016 Winter Simulation Conference, WSC 2016, Arlington, United States, 12/11/16. https://doi.org/10.1109/WSC.2016.7822111

Simulation analytics for virtual statistics via K nearest neighbors. / Lin, Yujing; Nelson, Barry L.
2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016. ed. / Theresa M. Roeder; Peter I. Frazier; Robert Szechtman; Enlu Zhou. Institute of Electrical and Electronics Engineers Inc., 2016. p. 448-459 7822111 (Proceedings - Winter Simulation Conference; Vol. 0).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Simulation analytics for virtual statistics via K nearest neighbors

AU - Lin, Yujing

AU - Nelson, Barry L.

PY - 2016/7/2

Y1 - 2016/7/2

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/85014223551

UR - https://www.scopus.com/inward/citedby.url?scp=85014223551&partnerID=8YFLogxK

U2 - 10.1109/WSC.2016.7822111

DO - 10.1109/WSC.2016.7822111

M3 - Conference contribution

T3 - Proceedings - Winter Simulation Conference

SP - 448

EP - 459

BT - 2016 Winter Simulation Conference

A2 - Roeder, Theresa M.

A2 - Frazier, Peter I.

A2 - Szechtman, Robert

A2 - Zhou, Enlu

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 Winter Simulation Conference, WSC 2016

Y2 - 11 December 2016 through 14 December 2016

ER -

Lin Y, Nelson BL. Simulation analytics for virtual statistics via K nearest neighbors. In Roeder TM, Frazier PI, Szechtman R, Zhou E, editors, 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 448-459. 7822111. (Proceedings - Winter Simulation Conference). doi: 10.1109/WSC.2016.7822111

Simulation analytics for virtual statistics via K nearest neighbors

Abstract

Publication series

Other

Funding

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this