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Author Rossetti, M. D. ♦ Hill, R. R. ♦ Johansson, B. ♦ Dunkin, A. ♦ Ingalls, R. G. ♦ Staum, Jeremy
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Stochastic Kriging ♦ Better Simulation Metamodeling ♦ Metamodeling Methodology ♦ Global Metamodeling ♦ Misspecified Model ♦ Advanced Tutorial Explains Regression ♦ Simulation Output ♦ Future Research Direction ♦ Square Regression ♦ Stochastic Simulation
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. 1 INTRODUCTION: SIMULATION
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study