15.6 Selection of Variables for Cluster Analysis

# Fig. 15.9.: Variable clustering library(StatDA) data(kola.background) data(ohorizon) el=c("Ag","Al","As","Ba","Bi","Ca","Cd","Co","Cr","Cu","Fe","Hg","K", "La","Mg","Mn","Mo","LOI","Na","Ni","P","Pb","Rb","S","Sb","Si","Sr","Th", "Tl","U","V","Y","Zn") x=scale(log10(ohorizon[,el])) set.seed(100) resvarall=Mclust(x,3:6) X=ohorizon[,"XCOO"] Y=ohorizon[,"YCOO"] # true representation of x and y axis of map for plot xwid=diff(range(X))/12e4 ywid=diff(range(Y))/12e4 pdf("fig-15-9.pdf",width=2*xwid,height=1*ywid) par(mfrow=c(1,2),mar=c(1.5,1.5,1.5,1.5)) # NEW MAP plot(X,Y,frame.plot=FALSE,xaxt="n",yaxt="n",xlab="",ylab="",type="n") plotbg(map.col=c("gray","gray","gray","gray"),add.plot=T) resvaral <- resvarall$cl resvaral[resvarall$cl==1] <- 2 resvaral[resvarall$cl==2] <- 3 resvaral[resvarall$cl==3] <- 4 resvaral[resvarall$cl==4] <- 16 resvaral[resvarall$cl==5] <- 1 resvaral[resvarall$cl==6] <- 15 points(ohorizon[,"XCOO"],ohorizon[,"YCOO"],pch=resvaral,cex=0.8) # Legend text(752000,7880000,"All variables",cex=1) # scalebar scalebar(761309,7373050,861309,7363050,shifttext=-0.5,shiftkm=37e3,sizetext=0.8) # North arrow Northarrow(362602,7818750,362602,7878750,362602,7838750,Alength=0.15,Aangle=15,Alwd=1.3,Tcex=1.6) el=c("Cu","Co","Ni") x=scale(log10(ohorizon[,el])) set.seed(100) resvarsel=Mclust(x,3:3) # NEW MAP plot(X,Y,frame.plot=FALSE,xaxt="n",yaxt="n",xlab="",ylab="",type="n") plotbg(map.col=c("gray","gray","gray","gray"),add.plot=T) resvarse <- resvarsel$cl resvarse[resvarsel$cl==1] <- 1 resvarse[resvarsel$cl==2] <- 3 resvarse[resvarsel$cl==3] <- 15 points(ohorizon[,"XCOO"],ohorizon[,"YCOO"],pch=resvarse,cex=0.8) # Legend text(752000,7880000,"Co, Cu, Ni",cex=1) # scalebar scalebar(761309,7373050,861309,7363050,shifttext=-0.5,shiftkm=37e3,sizetext=0.8) # North arrow Northarrow(362602,7818750,362602,7878750,362602,7838750,Alength=0.15,Aangle=15,Alwd=1.3,Tcex=1.6) dev.off()