Isbn: 9781032242552 - Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences (chapman & Hall/crc Texts in Statistical Science) (18 results)

Language: English
Published by Chapman and Hall/CRC, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
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Language: English
Published by Chapman and Hall/CRC, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by Chapman and Hall/CRC, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by Chapman and Hall/CRC, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by Chapman and Hall/CRC, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by Taylor & Francis Ltd, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by Chapman and Hall/CRC, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by Chapman and Hall/CRC, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by Taylor and Francis Ltd, GB, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
- First Edition
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Paperback. Condition: New. 1st. Surrogates: a graduate textbook, or professional handbook, on topics at the interface between machine learning, spatial statistics, computer simulation, meta-modeling (i.e., emulation), design of experiments, and optimization. Experimentation through simulation, "human out-of-the-loop" statistical support (focusing on the science), management of dynamic processes, online and real-time analysis, automation, and practical application are at the forefront. Topics include:Gaussian process (GP) regression for flexible nonparametric and nonlinear modeling.Applications to uncertainty quantification, sensitivity analysis, calibration of computer models to field data, sequential design/active learning and (blackbox/Bayesian) optimization under uncertainty. Advanced topics include treed partitioning, local GP approximation, modeling of simulation experiments (e.g., agent-based models) with coupled nonlinear mean and variance (heteroskedastic) models. Treatment appreciates historical response surface methodology (RSM) and canonical examples, but emphasizes contemporary methods and implementation in R at modern scale.Rmarkdown facilitates a fully reproducible tour, complete with motivation from, application to, and illustration with, compelling real-data examples.Presentation targets numerically competent practitioners in engineering, physical, and biological sciences. Writing is statistical in form, but the subjects are not about statistics. Rather, they're about prediction and synthesis under uncertainty; about visualization and information, design and decision making, computing and clean code. …

Language: English
Published by Routledge 2021-12-13, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by Chapman and Hall/CRC, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by Chapman and Hall/CRC, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by Chapman and Hall/CRC, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by Chapman & Hall, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
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Language: English
Published by CRC Press, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
- Print on Demand
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Language: English
Published by CRC Press, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
- Print on Demand
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Language: English
Published by CRC Press, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
- Print on Demand
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Robert B. Gramacy is a professor of Statistics in the College of Science at Virginia Tech. Research interests include Bayesian modeling methodology, statistical computing, Monte Carlo inference, nonparametric regression, sequential design, and optimizati.…

Language: English
Published by Chapman and Hall/CRC, 2021
Series: Book 69 of 59 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
- Print on Demand
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Taschenbuch. Condition: Neu. Surrogates | Gaussian Process Modeling, Design, and Optimization for the Applied Sciences | Robert B. Gramacy | Taschenbuch | Englisch | 2021 | Chapman and Hall/CRC | EAN 9781032242552 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …