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Data X:
100.00 127.27 109.09 136.36 100.00 118.18 136.36 100.00 127.27 118.18 136.36 145.45 154.55 100.00 145.45 118.18 154.55 145.45 154.55 172.73 163.64 172.73 145.45 136.36 145.45 145.45 154.55 181.82 181.82 172.73 154.55 163.64 172.73 154.55 181.82 190.91 218.18 227.27 227.27 236.36 200.00 227.27 254.55 254.55 263.64 272.73 281.82 263.64 245.45 200.00 227.27 209.09 236.36 209.09 200.00 163.64 163.64 181.82 145.45 163.64
Data Y:
100.00 98.86 96.87 103.18 104.66 103.74 103.87 98.10 98.91 109.43 104.89 88.63 97.03 93.79 97.61 98.17 96.31 97.82 87.52 85.71 89.15 90.65 92.74 80.00 84.33 93.26 115.89 105.21 94.23 106.12 94.41 101.30 98.43 107.94 102.82 92.33 97.48 88.37 92.50 81.48 92.55 98.96 77.28 91.01 81.21 88.41 96.02 91.59 86.30 86.37 105.41 76.73 93.26 95.02 84.32 93.24 89.81 111.66 103.23 103.21
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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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