Moving Least Squares regression for high dimensional simulation metamodeling

Peter Salemi*, Barry L. Nelson, Jeremy Staum

*Corresponding author for this work

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

5 Scopus citations

Abstract

Interpolation and smoothing methods form the basis of simulation metamodeling. In high dimensional metamodeling problems, larger numbers of design points are needed to build an accurate metamodel. This paper introduces a procedure to implement a smoothing method called Moving Least Squares regression in high dimensional metamodeling problems with a large number of design points. We test the procedure with two queueing examples: a multi-product M/G/1 queue and a multi-product Jackson network.

Original languageEnglish (US)
Title of host publicationProceedings of the 2012 Winter Simulation Conference, WSC 2012
DOIs
StatePublished - 2012
Event2012 Winter Simulation Conference, WSC 2012 - Berlin, Germany
Duration: Dec 9 2012Dec 12 2012

Publication series

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

Other

Other2012 Winter Simulation Conference, WSC 2012
CountryGermany
CityBerlin
Period12/9/1212/12/12

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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