{"author_url":"https://blog.hatena.ne.jp/ryamada22/","url":"https://ryamada22.hatenablog.jp/entry/20110811/1312950806","height":"190","type":"rich","description":"\u91cd\u56de\u5e30 Multiple Linear Regression # \u91cd\u56de\u5e30 multiple linear regression n<-6 m<-4 X<-matrix(runif(n*m),n,m) m2<-2 Y<-matrix(runif(n*m2),n,m2) B<-solve(t(X)%*%X)%*%t(X)%*%Y Y-X%*%B # n<m \u3068\u3059\u308b\u3068\u89e3\u3051\u306a\u3044 m<-n+1 X<-matrix(runif(n*m),n,m) m2<-2 Y<-matrix(runif(n*m2),n,m2) B<-solve(t(X)%*%X)%*%t(X)%*%Y Y-X%*%B PCR \u3053\u3061\u3089\u306b\u2026","version":"1.0","title":"PCR(Principal Component Regression)\u3068PLSR(Partial Least Squares Regression","width":"100%","provider_name":"Hatena Blog","categories":["R","\u30aa\u30df\u30c3\u30af\u30b9"],"blog_title":"ryamada\u306e\u907a\u4f1d\u5b66\u30fb\u907a\u4f1d\u7d71\u8a08\u5b66\u30e1\u30e2","published":"2011-08-11 13:33:26","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fryamada22.hatenablog.jp%2Fentry%2F20110811%2F1312950806\" title=\"PCR(Principal Component Regression)\u3068PLSR(Partial Least Squares Regression - ryamada\u306e\u907a\u4f1d\u5b66\u30fb\u907a\u4f1d\u7d71\u8a08\u5b66\u30e1\u30e2\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","blog_url":"https://ryamada22.hatenablog.jp/","author_name":"ryamada22","provider_url":"https://hatena.blog","image_url":null}