{"title":"一般协方差结构下具有定性因子的多响应线性模型的D最优设计","authors":"Rong-Xian Yue, Xin Liu, Kashinath Chatterjee","doi":"10.1007/s10255-023-1089-9","DOIUrl":null,"url":null,"abstract":"<div><p>This paper considers a linear regression model involving both quantitative and qualitative factors and an <i>m</i>-dimensional response variable <b><i>y</i></b>. The main purpose of this paper is to investigate <i>D</i>-optimal designs when the levels of the qualitative factors interact with the levels of the quantitative factors. Under a general covariance structure of the response vector <b><i>y</i></b>, here we establish that the determinant of the information matrix of a product design can be separated into two parts corresponding to the two marginal designs. Moreover, it is also proved that <i>D</i>-optimal designs do not depend on the covariance structure if we assume hierarchically ordered system of regression models.</p></div>","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"D-optimal Designs for Multiresponse Linear Models with a Qualitative Factor Under General Covariance Structure\",\"authors\":\"Rong-Xian Yue, Xin Liu, Kashinath Chatterjee\",\"doi\":\"10.1007/s10255-023-1089-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper considers a linear regression model involving both quantitative and qualitative factors and an <i>m</i>-dimensional response variable <b><i>y</i></b>. The main purpose of this paper is to investigate <i>D</i>-optimal designs when the levels of the qualitative factors interact with the levels of the quantitative factors. Under a general covariance structure of the response vector <b><i>y</i></b>, here we establish that the determinant of the information matrix of a product design can be separated into two parts corresponding to the two marginal designs. Moreover, it is also proved that <i>D</i>-optimal designs do not depend on the covariance structure if we assume hierarchically ordered system of regression models.</p></div>\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2023-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10255-023-1089-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"100","ListUrlMain":"https://link.springer.com/article/10.1007/s10255-023-1089-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
D-optimal Designs for Multiresponse Linear Models with a Qualitative Factor Under General Covariance Structure
This paper considers a linear regression model involving both quantitative and qualitative factors and an m-dimensional response variable y. The main purpose of this paper is to investigate D-optimal designs when the levels of the qualitative factors interact with the levels of the quantitative factors. Under a general covariance structure of the response vector y, here we establish that the determinant of the information matrix of a product design can be separated into two parts corresponding to the two marginal designs. Moreover, it is also proved that D-optimal designs do not depend on the covariance structure if we assume hierarchically ordered system of regression models.