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Data X:
105.8 105.7 105.5 105.4 105.4 105.6 105.7 105.6 105.6 105.6 105.4 105.4 105.9 106.6 107.3 107.8 108.1 108.4 108.8 109 109 109 108.8 108.4 107.9 107.5 107.2 107.1 107.2 107.4 107.5 107.5 107.8 108.6 109.7 110.6 111.2 111.8 112.7 113.8 115.1 116.2 117.2 118.5 120.2 122.1 123.7 125 126 127 128 129.1 130.1 130.7 131 131.5 132.4 132.8 132.7 132.7
Data Y:
98 97 96 96 96 96 96 96 96 97 97 98 99 101 102 103 104 105 106 107 106 105 105 105 105 105 105 105 105 106 106 106 105 105 107 108 110 111 111 112 112 112 112 113 115 117 118 118 118 118 118 118 119 121 121 122 123 123 124 124
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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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