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2018 | OriginalPaper | Buchkapitel

3. Empirical Best Linear Unbiased Prediction of Computer Simulator Output

verfasst von : Thomas J. Santner, Brian J. Williams, William I. Notz

Erschienen in: The Design and Analysis of Computer Experiments

Verlag: Springer New York

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Abstract

This chapter and Chap. 4 discuss techniques for predicting output for a computer simulator based on “training” runs from the model. Knowing how to predict computer output is a prerequisite for answering most practical research questions that involve computer simulators including those listed in Sect. 1.3. As an example where the prediction methods described below will be central, Chap. 6 will present a sequential design for a computer experiment to find input conditions \(\boldsymbol{x}\) that maximize a computer output which requires prediction of \(y(\boldsymbol{x})\) at all untried sites.

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Vorheriges Kapitel Stochastic Process Models for Describing Computer Simulator Output

Nächstes Kapitel Bayesian Inference for Simulator Output

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Titel: Empirical Best Linear Unbiased Prediction of Computer Simulator Output
verfasst von: Thomas J. Santner
Brian J. Williams
William I. Notz
Verlag: Springer New York
Buch: The Design and Analysis of Computer Experiments
Print ISBN: 978-1-4939-8845-7

Electronic ISBN: 978-1-4939-8847-1

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-1-4939-8847-1_3

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