dat<-read.table("http://www.matsuka.info/data_folder/tdkPCA01.txt")
dat.pca<-princomp(dat)
biplot(dat.pca)
dat.pca$score
dat.pca$loadings
scoreP1S1 = dat.pca$loadings[1,1]*(dat[1,1]-mean(dat$writing))+
dat.pca$loadings[2,1]*(dat[1,2]-mean(dat$thesis))+
dat.pca$loadings[3,1]*(dat[1,3]-mean(dat$interview))
scoreP2S2 = dat.pca$loadings[1,2]*(dat[2,1]-mean(dat$writing))+
dat.pca$loadings[2,2]*(dat[2,2]-mean(dat$thesis))+
dat.pca$loadings[3,2]*(dat[2,3]-mean(dat$interview))
dat<-read.csv("http://www.matsuka.info/data_folder/tdkCFA.csv")
dat.pca<-princomp(dat)
screeplot(dat.pca,type="lines")
biplot(dat.pca)
biplot(dat.pca,choices=c(2,3))
dat2<-read.table("http://www.matsuka.info/data_folder/tdkPCA01.txt")
dat2[,1]=dat2[,1]*0.1
dat2.pca<-princomp(dat2)
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