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Data X:
72.5 72.0 98.8 75.2 81.2 88.0 54.6 68.6 101.5 93.4 84.5 91.4 64.5 64.5 117.3 73.5 79.7 102.6 57.9 73.1 102.4 82.3 89.1 84.7 81.4 67.5 113.9 83.8 73.9 103.9 67.9 62.5 125.4 79.1 106.3 96.2 94.3 85.6 117.4 88.5 124.2 119.3 76.8 70.6 122.1 109.5 119.9 102.3 79.6 78.2 103.6 77.8 99.1 105.7 84.1 88.7 108.0 98.1 101.0 82.0
Data Y:
95.9 95.3 100.4 97.3 82.3 97.0 93.5 90.9 107.8 110.9 98.1 106.5 93.4 95.7 109.0 97.6 92.7 107.5 91.7 95.7 111.4 106.0 104.8 108.7 97.3 97.1 106.1 98.6 98.5 105.5 86.2 98.3 111.3 105.0 105.7 103.5 96.9 98.1 111.7 94.7 104.2 109.7 91.3 102.6 114.2 115.8 113.5 107.1 104.5 101.9 116.0 102.0 108.1 112.9 104.5 109.1 113.4 123.9 117.7 108.3
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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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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