Design analysis computer experiments von thomas santner (11 Ergebnisse)

Hardcover. Zustand: 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. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Zustand: 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.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Hardback. Zustand: 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.…

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

Hardback. Zustand: 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.…