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Data X:
126.2 127.0 127.1 123.6 125.0 134.7 140.7 137.9 142.1 137.5 136.4 140.7 120.0 123.8 132.2 136.4 144.2 144.9 138.9 129.3 133.3 137.5 140.0 146.3 124.6 130.2 139.0 149.1 151.9 149.0 127.8 113.8 117.5 123.2 127.3 131.5 110.8 112.7 116.9 127.3 130.8 130.6 124.1 113.8 112.3 112.5 112.7 120.4 104.6 107.9 108.5 110.9 111.5 124.5 133.3 125.9 121.1 108.9 105.5 114.8
Data Y:
111.2 116.7 114.8 100.0 98.8 106.3 119.5 120.7 121.1 112.4 108.2 113.6 106.7 114.3 117.3 109.6 109.9 112.5 116.1 112.0 113.3 107.9 108.2 114.8 105.6 111.9 113.6 108.4 111.1 112.5 112.6 108.7 108.9 104.5 105.9 111.1 102.2 108.3 112.3 110.8 108.6 103.8 96.6 88.0 85.6 88.8 92.9 98.8 88.8 90.5 87.7 81.9 80.2 86.3 94.3 94.6 92.2 88.8 88.2 96.3
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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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