@inproceedings{0864581d7e8c4061b639df79a7f8bf11,
title = "Tutorial: Metamodeling for Simulation",
abstract = "Metamodels are fast-to-compute mathematical models that are designed to mimic the input-output behavior of discrete-event or other complex simulation models. Linear regression metamodels have the longest history, but other model forms include Gaussian process regression and neural networks. This introductory tutorial highlights basic issues in choosing a metamodel type and specific form, and making simulation runs to fit the metamodel. The tutorial ends with advice on validation, and suggestions on further reading to expand your understanding of these methods.",
author = "Barton, \{Russell R.\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 Winter Simulation Conference, WSC 2022 ; Conference date: 11-12-2022 Through 14-12-2022",
year = "2022",
doi = "10.1109/WSC57314.2022.10015386",
language = "English (US)",
series = "Proceedings - Winter Simulation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1268--1282",
editor = "B. Feng and G. Pedrielli and Y. Peng and S. Shashaani and E. Song and C.G. Corlu and L.H. Lee and E.P. Chew and T. Roeder and P. Lendermann",
booktitle = "Proceedings of the 2022 Winter Simulation Conference, WSC 2022",
address = "United States",
}