Design and Modeling for Computer Experiments
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A01=Agus Sudjianto
A01=Kai-Tai Fang
A01=Runze Li
advanced computer experiment analysis
array
Author_Agus Sudjianto
Author_Kai-Tai Fang
Author_Runze Li
carlo
Category=UGK
Category=UMB
Center L2 Discrepancy
Computer Experiments
Crank Angle
Data Set
domain
engineering simulations
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
experimental
experimental methodology
Functional Linear Model
hypercube
L1 Penalty
latin
Latin Hypercube
Latin Hypercube Design
Latin Hypercube Sampling
Latin Square Method
Latin Squares
Local Polynomial Regression
matrix algebra applications
Maximin Distance
Maximin Distance Design
Maximum Entropy Designs
method
Modeling Computer Experiments
Optimal Latin Hypercube Designs
orthogonal
Orthogonal Array
quasi-monte
quasi-Monte Carlo Methods
Scad Penalty
Scad Penalty Function
sensitivity analysis
space-filling designs
Spatial Temporal Model
Spline Regression
statistical modeling
U-type Design
uniform
Uniform Design
Product details
- ISBN 9781584885467
- Weight: 600g
- Dimensions: 156 x 234mm
- Publication Date: 14 Oct 2005
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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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 experiment design are available, those interested in applying proposed methodologies need a practical presentation and straightforward guidance on analyzing and interpreting experiment results.
Written by authors with strong academic reputations and real-world practical experience, Design and Modeling for Computer Experiments is exactly the kind of treatment you need. The authors blend a sound, modern statistical approach with extensive engineering applications and clearly delineate the steps required to successfully model a problem and provide an analysis that will help find the solution. Part I introduces the design and modeling of computer experiments and the basic concepts used throughout the book. Part II focuses on the design of computer experiments. The authors present the most popular space-filling designs - like Latin hypercube sampling and its modifications and uniform design - including their definitions, properties, construction and related generating algorithms. Part III discusses the modeling of data from computer experiments. Here the authors present various modeling techniques and discuss model interpretation, including sensitivity analysis. An appendix reviews the statistics and mathematics concepts needed, and numerous examples clarify the techniques and their implementation.
The complexity of real physical systems means that there is usually no simple analytic formula that sufficiently describes the phenomena. Useful both as a textbook and professional reference, this book presents the techniques you need to design and model computer experiments for practical problem solving.
Kai-Tai Fang, Runze Li, Agus Sudjianto
