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WIREs Computational Statistics, 2010
AbstractThe purpose of this article is to provide a survey of the various stages in the development of response surface methodology (RSM). The coverage of these stages is organized in three parts that describe the evolution of RSM since its introduction in the early 1950s.
André I. Khuri, Siuli Mukhopadhyay
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AbstractThe purpose of this article is to provide a survey of the various stages in the development of response surface methodology (RSM). The coverage of these stages is organized in three parts that describe the evolution of RSM since its introduction in the early 1950s.
André I. Khuri, Siuli Mukhopadhyay
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2012
Response surface modelling is introduced and its bond to design of experiments is discussed. Several RSM techniques are presented from a theoretical point of view throughout the chapter. Among the various techniques described the typical approximation by least squares method is found, as well as the different weighted-average interpolating methods such
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Response surface modelling is introduced and its bond to design of experiments is discussed. Several RSM techniques are presented from a theoretical point of view throughout the chapter. Among the various techniques described the typical approximation by least squares method is found, as well as the different weighted-average interpolating methods such
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Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP, 2020
G. Oehlert
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G. Oehlert
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Empirical Model‐Building and Response Surfaces
, 1988E. Shoesmith, G. Box, N. Draper
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2020
In this chapter, we discuss several state-of-the-art RSM methods for performance modeling of analog and AMS circuits. RSM aims to approximate a given PoI by the linear combination of a set of basis functions. If the number of training samples is much larger than the number of adopted basis functions, the model coefficients can be accurately estimated ...
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In this chapter, we discuss several state-of-the-art RSM methods for performance modeling of analog and AMS circuits. RSM aims to approximate a given PoI by the linear combination of a set of basis functions. If the number of training samples is much larger than the number of adopted basis functions, the model coefficients can be accurately estimated ...
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A Taxonomy of Global Optimization Methods Based on Response Surfaces
Journal of Global Optimization, 2001Donald R. Jones
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Structural finite element model updating by using response surfaces and radial basis functions
, 2016Lin-ren Zhou, Lei Wang, Lan Chen, J. Ou
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Multiple response surfaces for slope reliability analysis
, 2015Liang Li, Xuesong Chu
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