Analysis of Computer Experiments with Multiple Noise Sources

Christian Dehlendorff; Murat Kulahci; Klaus Kaae Andersen

doi:10.1002/qre.1035

Analysis of Computer Experiments with Multiple Noise Sources

Christian Dehlendorff, Murat Kulahci, Klaus Kaae Andersen

Research output: Contribution to journal › Conference article › Research › peer-review

Abstract

In this paper we present a modeling framework for analyzing computer models with two types of variations. The paper is based on a case study of an orthopedic surgical unit, which has both controllable and uncontrollable factors. Our results show that this structure of variation can be modeled effectively with linear mixed effects models and generalized additive models. Copyright (C) 2009 John Wiley & Sons, Ltd.

Original language	English
Journal	Quality and Reliability Engineering International
Volume	26
Issue number	2
Pages (from-to)	137-146
ISSN	0748-8017
DOIs	https://doi.org/10.1002/qre.1035
Publication status	Published - 2010
Event	Annual Meeting of the European-Network-for-Business-and-Industrial-Statistics - Athens, GREECE Duration: 1 Jan 2008 → … Conference number: 8th

Conference

Conference	Annual Meeting of the European-Network-for-Business-and-Industrial-Statistics
Number	8th
City	Athens, GREECE
Period	01/01/2008 → …

Keywords

discrete event simulation
response surface
computer experiments

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title = "Analysis of Computer Experiments with Multiple Noise Sources",

abstract = "In this paper we present a modeling framework for analyzing computer models with two types of variations. The paper is based on a case study of an orthopedic surgical unit, which has both controllable and uncontrollable factors. Our results show that this structure of variation can be modeled effectively with linear mixed effects models and generalized additive models. Copyright (C) 2009 John Wiley & Sons, Ltd.",

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AB - In this paper we present a modeling framework for analyzing computer models with two types of variations. The paper is based on a case study of an orthopedic surgical unit, which has both controllable and uncontrollable factors. Our results show that this structure of variation can be modeled effectively with linear mixed effects models and generalized additive models. Copyright (C) 2009 John Wiley & Sons, Ltd.

KW - discrete event simulation

KW - response surface

KW - computer experiments

U2 - 10.1002/qre.1035

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Analysis of Computer Experiments with Multiple Noise Sources

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