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Data X:
106.48 106.83 107.14 107.94 108.46 108.81 108.92 108.99 109.16 109.22 109.43 109.23 109.93 110.09 110.33 110.11 110.35 110.09 110.44 110.39 110.62 110.43 110.46 110.55 110.94 111.56 111.82 111.73 111.57 111.85 112.06 112.2 112.47 112.15 112.36 112.32 112.67 113.02 113.05 113.5 113.67 113.65 114 114.03 114.08 114.49 114.48 114.25 114.68 115.28 115.9 115.87 116.09 116.29 116.76 116.78 116.65 116.46 116.82 116.91
Data Y:
106.22 106.31 107.38 109.31 110.82 111.22 110.66 110.76 110.69 111.08 110.97 110.24 112.51 111.52 112.13 112.23 112.92 111.89 111.99 111.51 112.33 112.04 112.09 111.41 112.61 113.14 113.65 114.26 114.4 114.93 114.86 114.95 116.17 114.6 114.62 113.82 115.02 115.18 115.59 116.6 117.07 116.96 116.66 116.07 116.04 115.81 116.22 115.85 116.43 117.39 119.17 119.24 120.03 119.34 118.49 118.59 117.5 117.56 118.25 118.01
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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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