Design and Modeling for Computer Experiments

This book PDF is perfect for those who love Mathematics genre, written by Kai-Tai Fang and published by CRC Press which was released on 14 October 2005 with total hardcover pages 304. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Design and Modeling for Computer Experiments books below.

Design and Modeling for Computer Experiments
Design and Modeling for Computer Experiments
Author : Kai-Tai Fang
File Size : 55,5 Mb
Publisher : CRC Press
Language : English
Release Date : 14 October 2005
ISBN : 9781420034899
Pages : 304 pages
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Design and Modeling for Computer Experiments by Kai-Tai Fang Book PDF Summary

Computer simulations based on mathematical models have become ubiquitous across the engineering disciplines and throughout the physical sciences. Successful use of a simulation model, however, requires careful interrogation of the model through systematic computer experiments. While specific theoretical/mathematical examinations of computer experim

Design and Modeling for Computer Experiments

Design and Modeling for Computer Experiments by Kai-Tai Fang,Runze Li,Agus Sudjianto

Computer simulations based on mathematical models have become ubiquitous across the engineering disciplines and throughout the physical sciences. Successful use of a simulation model, however, requires careful interrogation of the model through systematic computer experiments. While specific theoretical/mathematical examinations of computer experim

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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

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This is a new edition of Kleijnen’s advanced expository book on statistical methods for the Design and Analysis of Simulation Experiments (DASE). Altogether, this new edition has approximately 50% new material not in the original book. More specifically, the author has made significant changes to the book’s organization, including

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Here, the authors explain the basic ideas so as to generate interest in modern problems of experimental design. The topics discussed include designs for inference based on nonlinear models, designs for models with random parameters and stochastic processes, designs for model discrimination and incorrectly specified (contaminated) models, as well as

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The Design and Analysis of Computer Experiments

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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

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Computer simulation experiments are essential to modern scientific discovery, whether that be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are meta-models of computer simulations, used to solve mathematical models that are too intricate to be worked by hand. Gaussian process (GP) regression is a supremely flexible tool for

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The Design and Analysis of Computer Experiments

The Design and Analysis of Computer Experiments by Thomas J. Santner,Brian J. Williams,William I. Notz

Download or read online The Design and Analysis of Computer Experiments written by Thomas J. Santner,Brian J. Williams,William I. Notz, published by Unknown which was released on 2014-01-15. Get The Design and Analysis of Computer Experiments Books now! Available in PDF, ePub and Kindle.

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The book provides necessary knowledge for readers interested in developing the theory of uniform experimental design. It discusses measures of uniformity, various construction methods of uniform designs, modeling techniques, design and modeling for experiments with mixtures, and the usefulness of the uniformity in block, factorial and supersaturated designs. Experimental design

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