Identifying Significant Effects in Unreplicated Regular Two-level Factorial Experiments

被引：0
|
作者：
Li, Hui [1 ,2 ,3 ]
Zhao, Sheng-li [1 ]
机构：
[1] Qufu Normal Univ, Sch Stat, Qufu 273165, Shandong, Peoples R China
[2] Nankai Univ, Sch Stat & Data Sci, LPMC, Tianjin 300071, Peoples R China
[3] Nankai Univ, KLMDASR, Tianjin 300071, Peoples R China
来源：
ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES | 2020年 / 36卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Two-level factorial experiment; factorial effect; significant effect; Monte Carlo;
D O I：
10.1007/s10255-020-0981-9
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The paper gives a new method to identify significant effects in two-level factorial experiments, and compares the new method with the exiting methods using Monte Carlo simulation. The existing methods only perform well under the assumption of effect sparsity, but the new method performs well without effect sparsity.
引用
收藏
页码：816 / 824
页数：9
相关论文
共 50 条
12345