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Data X:
90.21 93.24 95.60 97.58 100.81 101.65 102.08 100.18 101.36 103.46 106.59 107.24 107.84 110.08 114.34 120.00 124.78 128.21 127.48 124.39 116.83 121.13 126.39 129.92 135.43 137.43 140.42 145.42 147.35 142.58 150.25 153.71 151.23 149.32 137.53 140.60 145.14 134.34 134.72 125.81 121.77 120.24 126.24 124.39 114.68 99.24 99.71 96.94 71.92 65.92 60.96 62.35 59.26 54.65 61.01 67.15 66.42 67.77 75.05 79.95
Data Y:
95.40 99.31 101.80 100.53 102.28 101.89 98.08 98.98 100.02 100.58 100.67 100.46 98.47 102.01 103.28 103.70 104.64 106.31 107.16 108.10 104.90 105.27 107.37 110.01 114.11 116.22 118.06 119.35 120.48 117.02 121.66 127.88 128.58 130.42 126.28 129.31 132.59 125.91 127.88 119.59 118.46 116.31 120.72 122.21 115.00 107.99 109.98 106.01 87.58 82.17 81.99 80.08 73.35 69.01 76.23 80.10 81.96 82.79 89.42 91.90
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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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