Design of follow‐up experiments for improving model discrimination and parameter estimation
Design of follow‐up experiments for improving model discrimination and parameter estimation
复制标题
设计后续实验以改进模型辨别和参数估计
DOI：
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发表时间：
2004
期刊：
影响因子：
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通讯作者：
S. Chick
中科院分区：
文献类型：
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作者：
S. Ng;S. Chick
实验的一个目标是确定哪些设计参数对系统的平均性能影响最大。另一个目标是为响应模型获得良好的参数估计值，该响应模型量化了平均性能如何取决于有影响的参数。大多数实验设计技术每次只关注一个目标。本文提出了一种新的基于熵的后续实验设计准则，该准则联合识别重要参数并减小参数估计的方差。我们简化了计算正常的线性模型，确定一个近似，导致一个封闭的形式的解决方案。该标准适用于一个例子，从实验设计文献，一个已知的模型和重症监护设施模拟实验。© 2004 Wiley Periodicals，Inc.海军研究后勤，2004年
One goal of experimentation is to identify which design parameters most significantly influence the mean performance of a system. Another goal is to obtain good parameter estimates for a response model that quantifies how the mean performance depends on influential parameters. Most experimental design techniques focus on one goal at a time. This paper proposes a new entropy‐based design criterion for follow‐up experiments that jointly identifies the important parameters and reduces the variance of parameter estimates. We simplify computations for the normal linear model by identifying an approximation that leads to a closed form solution. The criterion is applied to an example from the experimental design literature, to a known model and to a critical care facility simulation experiment. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004