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Data X:
105.1 113.3 99.1 100.3 93.5 98.8 106.2 98.3 102.1 117.1 101.5 80.5 105.9 109.5 97.2 114.5 93.5 100.9 121.1 116.5 109.3 118.1 108.3 105.4 116.2 111.2 105.8 122.7 99.5 107.9 124.6 115 110.3 132.7 99.7 96.5 118.7 112.9 130.5 137.9 115 116.8 140.9 120.7 134.2 147.3 112.4 107.1 128.4 137.7 135 151 137.4 132.4 161.3 139.8 146 154.6 142.1 120.5
Data Y:
88.8 93.4 92.6 90.7 81.6 84.1 88.1 85.3 82.9 84.8 71.2 68.9 94.3 97.6 85.6 91.9 75.8 79.8 99 88.5 86.7 97.9 94.3 72.9 91.8 93.2 86.5 98.9 77.2 79.4 90.4 81.4 85.8 103.6 73.6 75.7 99.2 88.7 94.6 98.7 84.2 87.7 103.3 88.2 93.4 106.3 73.1 78.6 101.6 101.4 98.5 99 89.5 83.5 97.4 87.8 90.4 97.1 79.4 85
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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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