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  • Detecting Bias due to Input Modelling in Computer Simulation

    Rights statement: ©2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

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Detecting bias due to input modelling in computer simulation

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Published
Publication date3/12/2017
Host publication2017 Winter Simulation Conference (WSC)
Place of PublicationPiscataway, NJ, USA
PublisherIEEE Press
Pages1974-1985
Number of pages12
ISBN (electronic)9781538634288
ISBN (print)9781538634301
<mark>Original language</mark>English
EventWinter Simulation Conference 2017 - Red Rock Casino Resort & Spa, Las Vegas, United States
Duration: 3/12/2017 → 6/12/2017
Conference number: 50th
http://meetings2.informs.org/wordpress/wsc2017/

Conference

ConferenceWinter Simulation Conference 2017
Country/TerritoryUnited States
CityLas Vegas
Period3/12/17 → 6/12/17
Internet address

Conference

ConferenceWinter Simulation Conference 2017
Country/TerritoryUnited States
CityLas Vegas
Period3/12/17 → 6/12/17
Internet address

Abstract

Bias due to input modelling is almost always assumed negligible and ignored. It is known that increasing the amount of real-world data available for modelling input processes causes this form of bias to decrease faster than the variance due to input uncertainty. However, this does not mean bias is irrelevant when considering the error in a simulation performance measure caused by input modelling. In this paper we present a response surface approach to bias estimation in simulation models along with a diagnostic test for identifying, with controlled power, bias due to input modelling of a size that would be concerning to a practitioner.

Bibliographic note

©2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

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