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Extensions of D-optimal Minimal Designs for Symmetric Mixture Models

机译:对称混合物模型的D最优最小设计的扩展

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摘要

The purpose of mixture experiments is to explore the optimum blends of mixture components, which will provide desirable response characteristics in finished products. D-optimal minimal designs have been considered for a variety of mixture models, including Scheffé's linear, quadratic, and cubic models. Usually, these D-optimal designs are minimally supported since they have just as many design points as the number of parameters. Thus, they lack the degrees of freedom to perform the Lack of Fit tests. Also, the majority of the design points in D-optimal minimal designs are on the boundary: vertices, edges, or faces of the design simplex.In This Paper, Extensions Of The D-Optimal Minimal Designs Are Developed For A General Mixture Model To Allow Additional Interior Points In The Design Space To Enable Prediction Of The Entire Response SurfaceAlso a new strategy for adding multiple interior points for symmetric mixture models is proposed. We compare the proposed designs with two ten-point designs for the Lack of Fit test by simulations.
机译:混合物实验的目的是探索混合物成分的最佳共混物,这将为最终产品提供理想的响应特性。已经为各种混合模型(包括Scheffé的线性,二次和三次模型)考虑了D最优最小设计。通常,这些D最佳设计的支持最少,因为它们的设计点与参数数量一样多。因此,他们缺乏执行“缺乏适应性”测试的自由度。同样,D最优最小设计中的大多数设计点都在边界上:设计单纯形的顶点,边或面。本文为通用混合模型开发了D最优最小设计的扩展允许在设计空间中添加其他内部点以预测整个响应曲面。此外,还提出了为对称混合模型添加多个内部点的新策略。通过仿真,我们将拟议的设计与两个10点设计进行了拟合度测试的比较。

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