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AI 根据所提供的论文材料归类:摘要直接讨论邻居效应、处理间干扰及直接处理效应的实验设计。

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代码、数据与补充材料

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关注这篇论文的作者
Wei Zheng
Mingyao Ai
Kang Li

干扰模型中普遍最优圆周设计的判别

研究问题
在存在邻近处理效应和误差相关性的区组实验中,如何判别圆周设计的普遍最优性,并比较既有邻居平衡设计?
方法与思路
作者借助近似设计理论中的基准设计评价邻居平衡设计,并提出适用于伪对称及非伪对称设计的普遍最优性等价条件。
材料陈述的贡献
摘要称既有设计在同方差无相关误差下效率较高,但相关误差下可被其他设计超越,并给出不同规模及协方差下的最优性判别。
阅读关注点
应核对干扰模型如何区分直接与邻近效应、普遍最优性的准则、协方差条件,以及等价条件如何用于寻找可实施设计。
阅读边界
仅据 OpenAlex 索引摘要,稿件版本未注明;等价条件和效率差异数值未说明,不能推断存在一个对所有协方差均最优的设计。

原文摘要

Many applications of block designs exhibit neighbor and edge effects. A popular remedy is to use the circular design coupled with the interference model. The search for optimal or efficient designs has been intensively studied in recent years. The circular neighbor balanced designs at distances 1 and 2 (CNBD2), including orthogonal array of type I ($\mathrm{OA}_{I}$) of strength $2$, are the two major designs proposed in literature for the purpose of estimating the direct treatment effects. They are shown to be optimal within some reasonable subclasses of designs. By using benchmark designs in approximate design theory, we show that CNBD2 is highly efficient among all possible designs when the error terms are homoscedastic and uncorrelated. However, when the error terms are correlated, these designs will be outperformed significantly by other designs. Note that CNBD2 fall into the special catalog of pseudo symmetric designs, and they only exist when the number of treatments is larger than the block size and the number of blocks is multiple of some constants. In this paper, we elaborate equivalent conditions for any design, pseudo symmetric or not, to be universally optimal for any size of experiment and any covariance structure of the error terms. This result is novel for circular designs and sheds light on other similar models in the search for optimal or efficient asymmetric designs.

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