Identifying Significant Effects in Unreplicated Regular Two-level Factorial Experiments

被引：0

作者：

Hui LI ^{[1
,2
]}

Sheng-li ZHAO ^{[1
]}

机构：

[1] School of Statistics, Qufu Normal University

[2] School of Statistics and Data Science, LPMC and KLMDASR, Nankai University

来源：

Acta Mathematicae Applicatae Sinica | 2020年 / 36卷 / 04期

基金：

中国国家自然科学基金;

关键词：

D O I：

暂无

中图分类号：

O212.6 [试验分析与试验设计];

学科分类号：

020208 ; 070103 ; 0714 ;

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

页码：816 / 824

页数：9

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