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Analysis of Response Surface Designs to Outlier
2010 International Conference on E-Business and E-Government, 2010Response surface designs investigating the effects of several factors have widely application and make the researcher or analyst to control the factors or model the effects of the input variables on the response of the process. Outliers among the measurements can almost be inevitable and will frequently have a highly confusing effect on response ...
Juntao Fang, Zhen He 0001
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Response Surfaces and Robust Design
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 1999AbstractResponse surface methods can be applied for building both global and mid‐range approximation models, to be used in structural optimization as an interface between analysis tools and optimization algorithms. This approach is particularly promising in those areas, where the structural behaviour or analysis process exhibits noise, because ...
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Response Surface Designs for Experiments in Bioprocessing
Biometrics, 2005SummaryMany processes in the biological industries are studied using response surface methodology. The use of biological materials, however, means that run‐to‐run variation is typically much greater than that in many experiments in mechanical or chemical engineering and so the designs used require greater replication.
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Some Considerations in Optimal Response Surface Designs
Bulletin of the Malaysian Mathematical Sciences Society, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
AlKandari, Bashayer Y. +2 more
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Reinforcement of Response Surface Designs
Communications in Statistics - Simulation and Computation, 1989This paper investigates the effect of missing observations in response surface designs and suggests using reinforcement of the design matrix in advance to avoid the consequences of missing observations. The investigations are confined to a central composite design only.
Anant M. Kshirsagar, Min-Chu Lin
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1996
Publisher Summary This chapter focuses on response surface designs. When the mechanism that produced the data is either unknown or poorly understood, so that the mathematical form of the true response surface is unknown, an empirical model is often fitted to the data. An empirical model is usually linear in the parameters and often of polynomial form,
Norman R. Draper, Dennis K.J. Lin
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Publisher Summary This chapter focuses on response surface designs. When the mechanism that produced the data is either unknown or poorly understood, so that the mathematical form of the true response surface is unknown, an empirical model is often fitted to the data. An empirical model is usually linear in the parameters and often of polynomial form,
Norman R. Draper, Dennis K.J. Lin
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Discussion of “Response surface design evaluation and comparison”
Journal of Statistical Planning and Inference, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Response-surface experimental design
IEEE Potentials, 1992Response-surface experimental design is explained, and it is shown that it offers a powerful tool for efficiently characterizing and optimizing a complex process. Engineers end up with a picture and the ability to predict what will happen for any given set of operating conditions.
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Small response surface designs for metamodel estimation
European Journal of Operational Research, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Batmaz, I, Tunali, S
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A class of composite designs for response surface methodology
Computational Statistics & Data Analysis, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stelios D. Georgiou +2 more
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