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Data X:
106.8 113.7 102.5 96.6 92.1 95.6 102.3 98.6 98.2 104.5 84.0 73.8 103.9 106.0 97.2 102.6 89.0 93.8 116.7 106.8 98.5 118.7 90.0 91.9 113.3 113.1 104.1 108.7 96.7 101.0 116.9 105.8 99.0 129.4 83.0 88.9 115.9 104.2 113.4 112.2 100.8 107.3 126.6 102.9 117.9 128.8 87.5 93.8 122.7 126.2 124.6 116.7 115.2 111.1 129.9 113.3 118.5 133.5 102.1 102.4
Data Y:
112.6 113.8 107.8 103.2 103.3 101.2 107.7 110.4 101.9 115.9 89.9 88.6 117.2 123.9 100.0 103.6 94.1 98.7 119.5 112.7 104.4 124.7 89.1 97.0 121.6 118.8 114.0 111.5 97.2 102.5 113.4 109.8 104.9 126.1 80.0 96.8 117.2 112.3 117.3 111.1 102.2 104.3 122.9 107.6 121.3 131.5 89.0 104.4 128.9 135.9 133.3 121.3 120.5 120.4 137.9 126.1 133.2 146.6 103.4 117.2
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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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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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