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The design and analysis of computer ...

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The design and analysis of computer experiments

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	The design and analysis of computer experiments/ by Thomas J. Santner, Brian J. Williams, William I. Notz.
作者:	Santner, Thomas J.
其他作者:	Williams, Brian J.
出版者:	New York, NY :Springer New York : : 2018.,
面頁冊數:	xv, 436 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Experimental design. -
電子資源:	https://doi.org/10.1007/978-1-4939-8847-1
ISBN:	9781493988471

The design and analysis of computer experiments
Santner, Thomas J.

The design and analysis of computer experiments[electronic resource] /by Thomas J. Santner, Brian J. Williams, William I. Notz. - 2nd ed. - New York, NY :Springer New York :2018. - xv, 436 p. :ill., digital ;24 cm. - Springer series in statistics,0172-7397. - Springer series in statistics..

Physical Experiments and Computer Experiments -- Stochastic Process Models for Describing Simulator Output -- Empirical Best Linear Unbiased Prediction for Simulator Output -- Bayesian Inference for Simulator Output -- Space-Filling Designs for Computer Experiments -- Some Criterion-based Experimental Designs -- Sensitivity Analysis and Variable Screening -- Calibration -- Appendix A : List of Notation -- Appendix B: Mathematical Facts -- Appendix C: An Overview of Selected Optimization Algorithms -- Appendix D: An Introduction to Markov Chain Monte Carlo Algorithms -- Appendix E: A Primer on Constructing Quasi-Monte Carlo Sequences.

ISBN: 9781493988471

Standard No.: 10.1007/978-1-4939-8847-1doiSubjects--Topical Terms:

527680
Experimental design.

LC Class. No.: QA279 / .S268 2018

Dewey Class. No.: 519.5

The design and analysis of computer experiments
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245 1 4 $a The design and analysis of computer experiments $h [electronic resource] / $c by Thomas J. Santner, Brian J. Williams, William I. Notz.
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490 1 $a Springer series in statistics, $x 0172-7397
505 0 $a Physical Experiments and Computer Experiments -- Stochastic Process Models for Describing Simulator Output -- Empirical Best Linear Unbiased Prediction for Simulator Output -- Bayesian Inference for Simulator Output -- Space-Filling Designs for Computer Experiments -- Some Criterion-based Experimental Designs -- Sensitivity Analysis and Variable Screening -- Calibration -- Appendix A : List of Notation -- Appendix B: Mathematical Facts -- Appendix C: An Overview of Selected Optimization Algorithms -- Appendix D: An Introduction to Markov Chain Monte Carlo Algorithms -- Appendix E: A Primer on Constructing Quasi-Monte Carlo Sequences.
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