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Data X:
4.86 4.55 4.27 4.26 4.57 5.07 4.76 4.51 4.87 5.14 5.11 5.16 4.47 4.57 4.89 4.63 4.38 3.69 3.96 4.19 3.87 3.6 3.63 3.22 3.21 3.49 3.64 3.66 3.77 3.82 3.78 3.28 3.29 3.37 3.12 3.51 4.24 4.94 5.09 5.46 5.64 6.39 6.15 7.21 7.8 7.91 7.39 7.46 6.72 5.14 4.63 4.32 3.93 2.62 2.6 1.63 0.9 0.32 1.22 0.81
Data Y:
10.9 10.6 10.3 10.3 10.3 10.4 10.5 10.4 10.6 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.6 10.4 10.1 10 10 10 10 9.9 9.8 9.8 9.9 10.1 10 9.6 9.3 9 8.8 9 9.1 9.2 9.1 8.9 8.7 8.7 8.6 8.9 9.3 9.5 9.3 9.1 8.9 9.1 9.5 9.7 9.8 9.8 9.7 9.7 9.8 9.9
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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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