{"title":"主成分分析与偏最小二乘回归","authors":"W.J. Dunn III ∗ , D.R. Scott , W.G. Glen ∗","doi":"10.1016/0898-5529(89)90004-3","DOIUrl":null,"url":null,"abstract":"<div><p>The mathematics behind the techniques of principal component analysis and partial least squares regression is presented in detail, starting from the appropriate extrema conditions. The meaning of the resultant vectors and many of their mathematical interrelationships are also presented. Also, partial least squares is developed as a ‘modification’ of principal component analysis to underline the relationship between these two techniques. The adjacent paper includes applications.</p></div>","PeriodicalId":101214,"journal":{"name":"Tetrahedron Computer Methodology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1989-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0898-5529(89)90004-3","citationCount":"124","resultStr":"{\"title\":\"Principal components analysis and partial least squares regression\",\"authors\":\"W.J. Dunn III ∗ , D.R. Scott , W.G. Glen ∗\",\"doi\":\"10.1016/0898-5529(89)90004-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The mathematics behind the techniques of principal component analysis and partial least squares regression is presented in detail, starting from the appropriate extrema conditions. The meaning of the resultant vectors and many of their mathematical interrelationships are also presented. Also, partial least squares is developed as a ‘modification’ of principal component analysis to underline the relationship between these two techniques. The adjacent paper includes applications.</p></div>\",\"PeriodicalId\":101214,\"journal\":{\"name\":\"Tetrahedron Computer Methodology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1989-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/0898-5529(89)90004-3\",\"citationCount\":\"124\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Tetrahedron Computer Methodology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/0898552989900043\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tetrahedron Computer Methodology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0898552989900043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Principal components analysis and partial least squares regression
The mathematics behind the techniques of principal component analysis and partial least squares regression is presented in detail, starting from the appropriate extrema conditions. The meaning of the resultant vectors and many of their mathematical interrelationships are also presented. Also, partial least squares is developed as a ‘modification’ of principal component analysis to underline the relationship between these two techniques. The adjacent paper includes applications.
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