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Status已发表Published
TitleDetecting non-isomorphic orthogonal design
Creator
Date Issued2022-12-01
Source PublicationJournal of Statistical Planning and Inference
ISSN0378-3758
Volume221Pages:299-312
Abstract

We propose a new criterion "Entropy based on projection Hamming distance pattern", denoted as S(D), to evaluate and detect combinatorially non-isomorphic orthogonal designs. It is defined by the entropy based on the distribution of all Hamming distance patterns of projections, that provides a new perspective to evaluate orthogonal designs. Hamming distance pattern is incorporated in this new criterion since it has many connections with other criteria in the literature, such as the generalized word-length pattern and uniformity measures. To compare the detection performances, we adopt three orthogonal designs with different sizes, 18-run, 27-run and 32-run. Some non-isomorphic classes of 27-run and 32-run orthogonal designs are misclassified by S(D). Hence we adopt the projection Average Squared Correlation distribution as an amendment in the detection algorithm to improve the effectiveness.

KeywordEntropy Hamming distance pattern Isomorphism Orthogonal design Projection average squared correlation distribution
DOI10.1016/j.jspi.2022.05.003
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000876941400004
Scopus ID2-s2.0-85131757058
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/9793
CollectionFaculty of Science and Technology
Corresponding AuthorFang, Kaitai
Affiliation
1.Division of Science and Technology,BNU-HKBU United International College,Zhuhai,Jintong Road 2000,519000,China
2.Department of Biostatistics,University of North Carolina at Chapel Hill,United States
3.Department of Biostatistics,Bioinformatics and Biomathematics,Georgetown University,United States
4.The Key Lab of Random Complex Structures and Data Analysis,The Chinese Academy of Sciences,China
First Author AffilicationBeijing Normal-Hong Kong Baptist University
Corresponding Author AffilicationBeijing Normal-Hong Kong Baptist University
Recommended Citation
GB/T 7714
Lin, Yuxuan,Tang, Yihan,Zhang, Jiahuaet al. Detecting non-isomorphic orthogonal design[J]. Journal of Statistical Planning and Inference, 2022, 221: 299-312.
APA Lin, Yuxuan, Tang, Yihan, Zhang, Jiahua, & Fang, Kaitai. (2022). Detecting non-isomorphic orthogonal design. Journal of Statistical Planning and Inference, 221, 299-312.
MLA Lin, Yuxuan,et al."Detecting non-isomorphic orthogonal design". Journal of Statistical Planning and Inference 221(2022): 299-312.
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