用于基线参数化的两级正则设计
Two-Level Regular Designs for Baseline Parameterization.
作者信息
Zhao Shengli, Qin Mengru
机构信息
School of Statistics and Data Science, Qufu Normal University, Qufu 273165, China.
Zaozhuang No.2 Middle School, Zaozhuang 277000, China.
出版信息
Entropy (Basel). 2025 Jun 30;27(7):706. doi: 10.3390/e27070706.
Abstract
This paper considers two-level regular fractional factorial designs for baseline parameterization. Some new results that reveal relationships between the -values and word length pattern are developed. The new results help find two-level regular fractional factorial designs that are likely to be optimal under the -aberration criterion. Illustrative examples are included to demonstrate this point.
摘要
本文考虑用于基线参数化的二级正则分数析因设计。得出了一些揭示(p)值与字长模式之间关系的新结果。这些新结果有助于找到在(p -)偏差准则下可能最优的二级正则分数析因设计。文中包含示例来说明这一点。
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本文引用的文献
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