Design Analysis Computer Experiments (41 results)

Hardcover. Condition: Fair. 2003. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Condition: acceptable. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Acceptable condition! Any other included accessories are also in Acceptable condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear such as cover tears discoloration, staining, marks, scuffs, etc. All pages intact.…

Condition: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

XII, 283 p. Hardcover Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Springer Series in Statistics Vorauflage. Sprache: Englisch. …

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Hardcover. Condition: Very Good. 2. Auflage. Unread, some shelfwear. Immediately dispatched from Germany.

hardcover. Condition: New. In shrink wrap. Looks like an interesting title.

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Hardback. Condition: New. Second Edition 2018. This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers. New to this revised and expanded edition. An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples      . A new comparison of plug-in prediction methodologies for real-valued simulator output. An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions. A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization . A new chapter describing graphical and numerical sensitivity analysis tools. Substantial new material on calibration-based prediction and inference for calibration parameters .  Lists of software that can be used to fit models discussed in the book to aid practitioners.…

Condition: New. 2nd ed. 2018 edition NO-PA16APR2015-KAP.

Hardcover. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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Hardcover. Condition: Brand New. 2nd edition. 436 pages. 9.25x6.25x1.25 inches. In Stock.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers.New to this revised and expanded edition:- An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples - A new comparison of plug-in prediction methodologies for real-valued simulator output- An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions- A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization - A new chapter describing graphical and numerical sensitivity analysis tools- Substantial new material on calibration-based prediction and inference for calibration parameters - Lists of software that can be used to fit models discussed in the book to aid practitioners.…

Hardback. Condition: New. Second Edition 2018. This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers. New to this revised and expanded edition. An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples      . A new comparison of plug-in prediction methodologies for real-valued simulator output. An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions. A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization . A new chapter describing graphical and numerical sensitivity analysis tools. Substantial new material on calibration-based prediction and inference for calibration parameters .  Lists of software that can be used to fit models discussed in the book to aid practitioners.…