Title :
Better simulation metamodeling: The why, what, and how of stochastic kriging
Author_Institution :
Dept. of Ind. Eng. & Manage. Sci., Northwestern Univ., Evanston, IL, USA
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.
Keywords :
modelling; statistical analysis; stochastic processes; least squares regression; simulation metamodeling; stochastic kriging; Analytical models; Computational modeling; Industrial engineering; Metamodeling; Operations research; Predictive models; Response surface methodology; Steady-state; Stochastic processes; Stochastic systems;
Conference_Titel :
Simulation Conference (WSC), Proceedings of the 2009 Winter
Conference_Location :
Austin, TX
Print_ISBN :
978-1-4244-5770-0
DOI :
10.1109/WSC.2009.5429320