{"title":"基于R包的具有随机化限制的两水平多阶段析因设计的同构检验:IsoCheck","authors":"Pratishtha Batra, Neil Spencer, Pritam Ranjan","doi":"10.19139/soic-2310-5070-1494","DOIUrl":null,"url":null,"abstract":"\n \n \nFactorial designs are often used in various industrial and sociological experiments to identify significant factors and factor combinations that may affect the process re- sponse. In the statistics literature, several studies have investigated the analysis, con- struction, and isomorphism of factorial and fractional factorial designs. When there are multiple choices for a design, it is helpful to have an easy-to-use tool for identifying which are distinct, and which of those can be efficiently analyzed/has good theoretical properties. For this task, we present an R library called IsoCheck that checks the isomorphism of multi-stage 26n factorial experiments with randomization restrictions. Through representing the factors and their combinations as a finite projective geometry, IsoCheck recasts the problem of searching over all possible relabelings as a search over collineations, then exploits projective geometric properties of the space to make the search much more efficient. Furthermore, a bitstring representation of the factorial effects is used to characterize all possible rearrangements of designs, thus facilitating quick comparisons after relabeling. \nThis paper presents several detailed examples with R codes that illustrate the usage of the main functions in IsoCheck. Besides checking equivalence and isomorphism of 2^n multi-stage factorial designs, we demonstrate how the functions of the package can be used to create a catalog of all non-isomorphic designs, and good designs as per a suitably defined ranking criterion. \n \n \n","PeriodicalId":131002,"journal":{"name":"Statistics, Optimization & Information Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Isomorphism Check for Two-level Multi-Stage Factorial Designs with Randomization Restrictions via an R Package: IsoCheck\",\"authors\":\"Pratishtha Batra, Neil Spencer, Pritam Ranjan\",\"doi\":\"10.19139/soic-2310-5070-1494\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n \\nFactorial designs are often used in various industrial and sociological experiments to identify significant factors and factor combinations that may affect the process re- sponse. In the statistics literature, several studies have investigated the analysis, con- struction, and isomorphism of factorial and fractional factorial designs. When there are multiple choices for a design, it is helpful to have an easy-to-use tool for identifying which are distinct, and which of those can be efficiently analyzed/has good theoretical properties. For this task, we present an R library called IsoCheck that checks the isomorphism of multi-stage 26n factorial experiments with randomization restrictions. Through representing the factors and their combinations as a finite projective geometry, IsoCheck recasts the problem of searching over all possible relabelings as a search over collineations, then exploits projective geometric properties of the space to make the search much more efficient. Furthermore, a bitstring representation of the factorial effects is used to characterize all possible rearrangements of designs, thus facilitating quick comparisons after relabeling. \\nThis paper presents several detailed examples with R codes that illustrate the usage of the main functions in IsoCheck. Besides checking equivalence and isomorphism of 2^n multi-stage factorial designs, we demonstrate how the functions of the package can be used to create a catalog of all non-isomorphic designs, and good designs as per a suitably defined ranking criterion. \\n \\n \\n\",\"PeriodicalId\":131002,\"journal\":{\"name\":\"Statistics, Optimization & Information Computing\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistics, Optimization & Information Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.19139/soic-2310-5070-1494\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics, Optimization & Information Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.19139/soic-2310-5070-1494","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Isomorphism Check for Two-level Multi-Stage Factorial Designs with Randomization Restrictions via an R Package: IsoCheck
Factorial designs are often used in various industrial and sociological experiments to identify significant factors and factor combinations that may affect the process re- sponse. In the statistics literature, several studies have investigated the analysis, con- struction, and isomorphism of factorial and fractional factorial designs. When there are multiple choices for a design, it is helpful to have an easy-to-use tool for identifying which are distinct, and which of those can be efficiently analyzed/has good theoretical properties. For this task, we present an R library called IsoCheck that checks the isomorphism of multi-stage 26n factorial experiments with randomization restrictions. Through representing the factors and their combinations as a finite projective geometry, IsoCheck recasts the problem of searching over all possible relabelings as a search over collineations, then exploits projective geometric properties of the space to make the search much more efficient. Furthermore, a bitstring representation of the factorial effects is used to characterize all possible rearrangements of designs, thus facilitating quick comparisons after relabeling.
This paper presents several detailed examples with R codes that illustrate the usage of the main functions in IsoCheck. Besides checking equivalence and isomorphism of 2^n multi-stage factorial designs, we demonstrate how the functions of the package can be used to create a catalog of all non-isomorphic designs, and good designs as per a suitably defined ranking criterion.