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Data X:
96.80 114.10 110.30 103.90 101.60 94.60 95.90 104.70 102.80 98.10 113.90 80.90 95.70 113.20 105.90 108.80 102.30 99.00 100.70 115.50 100.70 109.90 114.60 85.40 100.50 114.80 116.50 112.90 102.00 106.00 105.30 118.80 106.10 109.30 117.20 92.50 104.20 112.50 122.40 113.30 100.00 110.70 112.80 109.80 117.30 109.10 115.90 96.00 99.80 116.80 115.70 99.40 94.30 91.00 93.20 103.10 94.10 91.80 102.70 82.60
Data Y:
8.00 8.10 7.70 7.50 7.60 7.80 7.80 7.80 7.50 7.50 7.10 7.50 7.50 7.60 7.70 7.70 7.90 8.10 8.20 8.20 8.20 7.90 7.30 6.90 6.60 6.70 6.90 7.00 7.10 7.20 7.10 6.90 7.00 6.80 6.40 6.70 6.60 6.40 6.30 6.20 6.50 6.80 6.80 6.40 6.10 5.80 6.10 7.20 7.30 6.90 6.10 5.80 6.20 7.10 7.70 7.90 7.70 7.40 7.50 8.00
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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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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