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Data X:
1.74 1.75 1.83 2.09 2.12 2.29 2.4 2.82 3.18 4 4.8 5.28 5.37 5.27 5.33 5.23 5.08 5.11 5.1 4.97 5 5.2 4.9 4.82 5.04 4.82 4.77 4.79 4.58 4.59 4.57 4.35 4.27 4.39 3.97 3.84 3.73 3.58 3.45 3.44 3.25 3.25 3.02 2.87 2.92 2.95 2.75 2.7 2.75 2.72 2.71 2.76 2.68 2.78 2.86 2.75 2.87 2.91 2.79 2.77
Data Y:
3.2 1.9 0 0.6 0.2 0.9 2.4 4.7 9.4 12.5 15.8 18.2 16.8 17.3 19.3 17.9 20.2 18.7 20.1 18.2 18.4 18.2 18.9 19.9 21.3 20 19.5 19.6 20.9 21 19.9 19.6 20.9 21.7 22.9 21.5 21.3 23.5 21.6 24.5 22.2 23.5 20.9 20.7 18.1 17.1 14.8 13.8 15.2 16 17.6 15 15 16.3 19.4 21.3 20.5 21.1 21.6 22.6
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R Code
n <- length(x) c <- array(NA,dim=c(401)) l <- array(NA,dim=c(401)) mx <- 0 mxli <- -999 for (i in 1:401) { l[i] <- (i-201)/100 if (l[i] != 0) { x1 <- (x^l[i] - 1) / l[i] } else { x1 <- log(x) } c[i] <- cor(x1,y) if (mx < abs(c[i])) { mx <- abs(c[i]) mxli <- l[i] } } c mx mxli if (mxli != 0) { x1 <- (x^mxli - 1) / mxli } else { x1 <- log(x) } r<-lm(y~x) se <- sqrt(var(r$residuals)) r1 <- lm(y~x1) se1 <- sqrt(var(r1$residuals)) bitmap(file='test1.png') plot(l,c,main='Box-Cox Linearity Plot',xlab='Lambda',ylab='correlation') grid() dev.off() bitmap(file='test2.png') plot(x,y,main='Linear Fit of Original Data',xlab='x',ylab='y') abline(r) grid() mtext(paste('Residual Standard Deviation = ',se)) dev.off() bitmap(file='test3.png') plot(x1,y,main='Linear Fit of Transformed Data',xlab='x',ylab='y') abline(r1) grid() mtext(paste('Residual Standard Deviation = ',se1)) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Box-Cox Linearity Plot',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'# observations x',header=TRUE) a<-table.element(a,n) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'maximum correlation',header=TRUE) a<-table.element(a,mx) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'optimal lambda(x)',header=TRUE) a<-table.element(a,mxli) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Residual SD (orginial)',header=TRUE) a<-table.element(a,se) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Residual SD (transformed)',header=TRUE) a<-table.element(a,se1) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Big Analytics Cloud Computing Center
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