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Data X:
77.21 81.52 100.00 87.41 64.23 71.41 51.22 48.64 55.06 63.65 54.83 40.83 83.69 74.18 85.44 79.01 67.92 80.67 53.28 54.31 57.99 60.25 58.05 34.12 95.26 89.41 106.63 83.90 83.21 75.88 58.09 54.10 57.26 67.79 56.72 34.51 91.31 80.10 97.17 78.26 77.23 82.16 65.17 55.56 59.97 75.42 59.51 38.84 93.18 91.74 93.80 101.36 79.60 83.25 64.49 54.04 62.03 70.43 49.78 35.72
Data Y:
101.26 101.08 100.00 98.02 96.76 97.84 107.03 110.09 110.45 110.09 107.03 107.21 106.49 106.13 105.23 103.24 102.16 102.52 111.89 113.33 113.15 110.27 107.21 107.57 106.85 106.31 104.50 103.42 103.24 103.24 111.71 112.79 111.71 105.95 101.98 100.36 101.08 98.92 95.86 94.77 92.07 89.91 100.00 101.80 97.66 94.95 91.89 92.61 93.15 91.53 88.83 88.29 84.50 86.13 95.14 96.22 93.33 91.17 90.45 92.97
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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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