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Data X:
100.0 100.6 114.2 91.5 94.7 110.6 71.3 104.1 112.3 110.2 112.9 95.1 103.1 101.9 100.4 106.9 100.7 114.3 73.3 105.9 113.9 112.1 117.5 97.5 112.3 106.9 120.9 92.7 110.9 116.5 77.1 113.1 115.9 123.5 123.6 101.5 121.0 112.2 126.0 101.8 117.9 122.2 82.7 120.5 120.3 134.2 128.2 100.5 126.0 122.9 106.1 130.4 121.3 126.1 88.7 118.7 129.3 136.2 123.0 103.5
Data Y:
100.0 95.3 90.7 88.4 86.0 86.0 95.3 95.3 88.4 86.0 81.4 83.7 95.3 88.4 86.0 83.7 76.7 79.1 86.0 86.0 79.1 76.7 69.8 69.8 76.7 69.8 67.4 65.1 58.1 60.5 65.1 62.8 55.8 51.2 48.8 48.8 53.5 48.8 46.5 44.2 39.5 41.9 48.8 46.5 41.9 39.5 37.2 37.2 41.9 39.5 39.5 34.9 34.9 34.9 41.9 41.9 39.5 39.5 41.9 46.5
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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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