{"title":"The PCovR biplot: a graphical tool for principal covariates regression.","authors":"Elisa Frutos-Bernal, José Luis Vicente-Villardón","doi":"10.1080/02664763.2024.2417978","DOIUrl":null,"url":null,"abstract":"<p><p>Biplots are useful tools because they provide a visual representation of both individuals and variables simultaneously, making it easier to explore relationships and patterns within multidimensional datasets. This paper extends their use to examine the relationship between a set of predictors <math><mrow><mi>X</mi></mrow> </math> and a set of response variables <math><mrow><mi>Y</mi></mrow> </math> using Principal Covariates Regression analysis (PCovR). The PCovR biplot provides a simultaneous graphical representation of individuals, predictor variables and response variables. It also provides the ability to examine the relationship between both types of variables in the form of the regression coefficient matrix.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"52 5","pages":"1144-1159"},"PeriodicalIF":1.2000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951325/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/02664763.2024.2417978","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
Biplots are useful tools because they provide a visual representation of both individuals and variables simultaneously, making it easier to explore relationships and patterns within multidimensional datasets. This paper extends their use to examine the relationship between a set of predictors and a set of response variables using Principal Covariates Regression analysis (PCovR). The PCovR biplot provides a simultaneous graphical representation of individuals, predictor variables and response variables. It also provides the ability to examine the relationship between both types of variables in the form of the regression coefficient matrix.
期刊介绍:
Journal of Applied Statistics provides a forum for communication between both applied statisticians and users of applied statistical techniques across a wide range of disciplines. These areas include business, computing, economics, ecology, education, management, medicine, operational research and sociology, but papers from other areas are also considered. The editorial policy is to publish rigorous but clear and accessible papers on applied techniques. Purely theoretical papers are avoided but those on theoretical developments which clearly demonstrate significant applied potential are welcomed. Each paper is submitted to at least two independent referees.