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Data X:
106.9 107.1 99.3 99.2 108.3 105.6 99.5 107.4 93.1 88.1 110.7 113.1 99.6 93.6 98.6 99.6 114.3 107.8 101.2 112.5 100.5 93.9 116.2 112.0 106.4 95.7 96.0 95.8 103.0 102.2 98.4 111.4 86.6 91.3 107.9 101.8 104.4 93.4 100.1 98.5 112.9 101.4 107.1 110.8 90.3 95.5 111.4 113.0 107.5 95.9 106.3 105.2 117.2 106.9 108.2 113.0 97.2 100.2 109.7 119.1
Data Y:
93.9 89.8 93.4 101.5 110.4 105.9 108.4 113.9 86.1 69.4 101.2 100.5 98.0 106.6 90.1 96.9 125.9 112.0 100.0 123.9 79.8 83.4 113.6 112.9 104.0 109.9 99.0 106.3 128.9 111.1 102.9 130.0 87.0 87.5 117.6 103.4 110.8 112.6 102.5 112.4 135.6 105.1 127.7 137.0 91.0 90.5 122.4 123.3 124.3 120.0 118.1 119.0 142.7 123.6 129.6 151.6 110.4 99.3 129.1 134.1
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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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