Using spatial considerations in the analysis of experiments
Using spatial considerations in the analysis of experiments
复制标题
在实验分析中考虑空间因素
DOI：
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复制
发表时间：
1991
期刊：
影响因子：
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通讯作者：
N. Cressie
中科院分区：
文献类型：
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作者：
M. Grondona;N. Cressie
经典的实验设计是基于随机化、阻塞和复制这三个概念。随机化努力消除（空间）相关性的影响，并为平等处理效果的假设提供有效的检验。最近，已经尝试使用治疗的空间位置来提高治疗对比估计器的效率。在本文中，我们展示了一种简单、灵活的空间建模方法来分析工业实验（例如，晶圆制造），可以产生比经典方法更有效的处理对比估计器。我们的分析基于经验广义最小二乘估计，其中空间相关参数由抗趋势响应数据估计。
Classical experimental design is based on the three concepts of randomization, blocking, and replication. Randomization endeavors to neutralize the effects of (spatial) correlation and yields valid tests for the hypothesis of equal treatment effects. More recently, attempts have been made to use the spatial location of treatments to improve the efficiencies of estimators of treatment contrasts. In this article, we show that a simple, flexible spatial-modeling approach to the analysis of industrial experiments (e.g., wafer fabrication) can yield more efficient estimators of the treatment contrasts than the classical approach. We base the analysis on empirical generalized least squares estimation, in which the spatial-dependence parameters are estimated from resistantly detrended response data.