{"title":"两级不规则设计的一种更有效的同构检验","authors":"Chunyan Wang, Robert W. Mee","doi":"10.5705/ss.202022.0200","DOIUrl":null,"url":null,"abstract":": In this paper, we propose some new necessary and sufficient conditions for identifying isomorphism in two-level fractional factorial designs, using a parallel flats structure. A new algorithm for checking isomorphism is provided accordingly. The proposed algorithm is simple and general, and can be used for either regular or nonregular designs. By taking advantage of the parallel flats structure when it exists, the method is much faster than current methods for assessing the isomorphism of nonregular two-level designs. Examples are given to illustrate the results. An efficient implementation of the proposed algorithm in Matlab can be found in the online Supplementary Material.","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"1 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A More Efficient Isomorphism Check for Two-Level Nonregular Designs\",\"authors\":\"Chunyan Wang, Robert W. Mee\",\"doi\":\"10.5705/ss.202022.0200\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": In this paper, we propose some new necessary and sufficient conditions for identifying isomorphism in two-level fractional factorial designs, using a parallel flats structure. A new algorithm for checking isomorphism is provided accordingly. The proposed algorithm is simple and general, and can be used for either regular or nonregular designs. By taking advantage of the parallel flats structure when it exists, the method is much faster than current methods for assessing the isomorphism of nonregular two-level designs. Examples are given to illustrate the results. An efficient implementation of the proposed algorithm in Matlab can be found in the online Supplementary Material.\",\"PeriodicalId\":49478,\"journal\":{\"name\":\"Statistica Sinica\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistica Sinica\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.5705/ss.202022.0200\",\"RegionNum\":3,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistica Sinica","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.5705/ss.202022.0200","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
A More Efficient Isomorphism Check for Two-Level Nonregular Designs
: In this paper, we propose some new necessary and sufficient conditions for identifying isomorphism in two-level fractional factorial designs, using a parallel flats structure. A new algorithm for checking isomorphism is provided accordingly. The proposed algorithm is simple and general, and can be used for either regular or nonregular designs. By taking advantage of the parallel flats structure when it exists, the method is much faster than current methods for assessing the isomorphism of nonregular two-level designs. Examples are given to illustrate the results. An efficient implementation of the proposed algorithm in Matlab can be found in the online Supplementary Material.
期刊介绍:
Statistica Sinica aims to meet the needs of statisticians in a rapidly changing world. It provides a forum for the publication of innovative work of high quality in all areas of statistics, including theory, methodology and applications. The journal encourages the development and principled use of statistical methodology that is relevant for society, science and technology.