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Data X:
103.63 103.64 103.66 103.77 103.88 103.91 103.91 103.92 104.05 104.23 104.30 104.31 104.31 104.34 104.55 104.65 104.73 104.75 104.75 104.76 104.94 105.29 105.38 105.43 105.43 105.42 105.52 105.69 105.72 105.74 105.74 105.74 105.95 106.17 106.34 106.37 106.37 106.36 106.44 106.29 106.23 106.23 106.23 106.23 106.34 106.44 106.44 106.48 106.50 106.57 106.40 106.37 106.25 106.21 106.21 106.24 106.19 106.08 106.13 106.09
Data Y:
103.34 103.38 103.64 104.04 104.11 104.11 104.11 104.17 105.16 105.86 106.11 106.11 106.11 106.13 106.67 106.85 106.97 107.02 107.02 107.07 107.76 108.10 108.18 108.22 108.22 108.17 108.31 108.31 108.36 108.46 108.46 108.46 109.43 109.55 109.62 109.70 109.70 109.56 109.92 109.81 109.78 109.80 109.80 109.79 110.40 110.95 111.07 111.09 111.10 111.01 111.01 111.35 111.42 111.24 111.24 111.47 111.57 111.96 112.02 112.02
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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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