relation: http://eprints.imtlucca.it/1444/
title: Metamodel variability analysis combining bootstrapping and validation techniques
creator: Dellino, Gabriella
creator: Meloni, Carlo
subject: HA Statistics
subject: QA Mathematics
description: Research on metamodel-based optimization has received considerably increasing interest in recent years, and has found successful applications in solving computationally expensive problems. The joint use of computer simulation experiments and metamodels introduces a source of uncertainty that we refer to as metamodel variability. To analyze and quantify this variability, we apply bootstrapping to residuals derived as prediction errors computed from cross-validation. The proposed method can be used with different types of metamodels, especially when limited knowledge on parameters’ distribution is available or when a limited computational budget is allowed. Our preliminary experiments based on the robust version of  the EOQ model show encouraging results.
publisher: ACM
date: 2012-12
type: Book Section
type: PeerReviewed
format: application/pdf
language: en
identifier: http://eprints.imtlucca.it/1444/1/wsc12poster-dellino_final.pdf
identifier:   Dellino, Gabriella and Meloni, Carlo  Metamodel variability analysis combining bootstrapping and validation techniques.   In:  WSC '12 Proceedings of the Winter Simulation Conference.   ACM.  ISBN 978-1-4673-4780-8      (2012)  
relation: http://dl.acm.org/citation.cfm?id=2430206