{"title":"最佳混合物的最佳设计:信息综述","authors":"Manisha Pal","doi":"10.3329/ijss.v24i1.71866","DOIUrl":null,"url":null,"abstract":"In a mixture experiment, the measured response is assumed to depend only on the relative proportions of ingredients or components present in the mixture. Scheffe´ (1958) first systematically considered this problem, and introduced different models and suitable designs. Optimum designs for the estimation of parameters in various mixture models are available in the literature. However, in a mixture experiment, interest is likely to be more on the optimum mixing proportions of the ingredients being used. In this exposition, we take the readers on a journey through the optimum designs developed for estimating the optimum mixture combination as accurately as possible under various mixture models.\nInternational Journal of Statistical Sciences, Vol.24(1), March, 2024, pp 1-14","PeriodicalId":512956,"journal":{"name":"International Journal of Statistical Sciences","volume":"8 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimum Designs for Optimum Mixtures: An Informative Review\",\"authors\":\"Manisha Pal\",\"doi\":\"10.3329/ijss.v24i1.71866\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a mixture experiment, the measured response is assumed to depend only on the relative proportions of ingredients or components present in the mixture. Scheffe´ (1958) first systematically considered this problem, and introduced different models and suitable designs. Optimum designs for the estimation of parameters in various mixture models are available in the literature. However, in a mixture experiment, interest is likely to be more on the optimum mixing proportions of the ingredients being used. In this exposition, we take the readers on a journey through the optimum designs developed for estimating the optimum mixture combination as accurately as possible under various mixture models.\\nInternational Journal of Statistical Sciences, Vol.24(1), March, 2024, pp 1-14\",\"PeriodicalId\":512956,\"journal\":{\"name\":\"International Journal of Statistical Sciences\",\"volume\":\"8 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Statistical Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3329/ijss.v24i1.71866\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Statistical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3329/ijss.v24i1.71866","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimum Designs for Optimum Mixtures: An Informative Review
In a mixture experiment, the measured response is assumed to depend only on the relative proportions of ingredients or components present in the mixture. Scheffe´ (1958) first systematically considered this problem, and introduced different models and suitable designs. Optimum designs for the estimation of parameters in various mixture models are available in the literature. However, in a mixture experiment, interest is likely to be more on the optimum mixing proportions of the ingredients being used. In this exposition, we take the readers on a journey through the optimum designs developed for estimating the optimum mixture combination as accurately as possible under various mixture models.
International Journal of Statistical Sciences, Vol.24(1), March, 2024, pp 1-14