{"title":"共线性数据的回归分析。","authors":"John Mandel","doi":"10.6028/jres.090.043","DOIUrl":null,"url":null,"abstract":"<p><p>This paper presents a technique based on the intuitively-simple concepts of Sample Domain and Effective Prediction Domain, for dealing with linear regression situations involving collinearity of any degree of severity. The Effective Prediction Domain (EPD) clarifies the concept of collinearity, and leads to conclusions that are quantitative and practically useful. The method allows for the presence of expansion terms among the regressors, and requires no changes when dealing with such situations.</p>","PeriodicalId":93321,"journal":{"name":"Journal of research of the National Bureau of Standards (1977)","volume":"90 6","pages":"465-476"},"PeriodicalIF":0.0000,"publicationDate":"1985-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6687607/pdf/jres-90-465.pdf","citationCount":"29","resultStr":"{\"title\":\"The Regression Analysis of Collinear Data.\",\"authors\":\"John Mandel\",\"doi\":\"10.6028/jres.090.043\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This paper presents a technique based on the intuitively-simple concepts of Sample Domain and Effective Prediction Domain, for dealing with linear regression situations involving collinearity of any degree of severity. The Effective Prediction Domain (EPD) clarifies the concept of collinearity, and leads to conclusions that are quantitative and practically useful. The method allows for the presence of expansion terms among the regressors, and requires no changes when dealing with such situations.</p>\",\"PeriodicalId\":93321,\"journal\":{\"name\":\"Journal of research of the National Bureau of Standards (1977)\",\"volume\":\"90 6\",\"pages\":\"465-476\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1985-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6687607/pdf/jres-90-465.pdf\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of research of the National Bureau of Standards (1977)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.6028/jres.090.043\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of research of the National Bureau of Standards (1977)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.6028/jres.090.043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a technique based on the intuitively-simple concepts of Sample Domain and Effective Prediction Domain, for dealing with linear regression situations involving collinearity of any degree of severity. The Effective Prediction Domain (EPD) clarifies the concept of collinearity, and leads to conclusions that are quantitative and practically useful. The method allows for the presence of expansion terms among the regressors, and requires no changes when dealing with such situations.
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