Better simulation metamodeling: The why, what, and how of stochastic kriging

Jeremy C Staum*

*Corresponding author for this work

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

54 Scopus citations

Abstract

Stochastic kriging is a methodology recently developed for metamodeling stochastic simulation. Stochastic kriging can partake of the behavior of kriging and of generalized least squares regression. This advanced tutorial explains regression, kriging, and stochastic kriging as metamodeling methodologies, emphasizing the consequences of misspecified models for global metamodeling. It provides an exposition of how to choose parameters in stochastic kriging and how to build a metamodel with it given simulation output, and discusses future research directions to enhance stochastic kriging.

Original languageEnglish (US)
Title of host publicationProceedings of the 2009 Winter Simulation Conference, WSC 2009
Pages119-133
Number of pages15
DOIs
StatePublished - Dec 1 2009
Event2009 Winter Simulation Conference, WSC 2009 - Austin, TX, United States
Duration: Dec 13 2009Dec 16 2009

Publication series

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

Other

Other2009 Winter Simulation Conference, WSC 2009
CountryUnited States
CityAustin, TX
Period12/13/0912/16/09

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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    Staum, J. C. (2009). Better simulation metamodeling: The why, what, and how of stochastic kriging. In Proceedings of the 2009 Winter Simulation Conference, WSC 2009 (pp. 119-133). [5429320] (Proceedings - Winter Simulation Conference). https://doi.org/10.1109/WSC.2009.5429320