@inproceedings{aec6afe595ad437e95b9c082cc99adff,
title = "Tutorial: Basics of Metamodeling",
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 a warning on potential pitfalls, and suggestions on further reading to expand your knowledge of metamodeling.",
author = "Barton, {Russell R.}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 Winter Simulation Conference, WSC 2023 ; Conference date: 10-12-2023 Through 13-12-2023",
year = "2023",
doi = "10.1109/WSC60868.2023.10408331",
language = "English (US)",
series = "Proceedings - Winter Simulation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1516--1530",
booktitle = "2023 Winter Simulation Conference, WSC 2023",
address = "United States",
}