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Data X:
13812 13031 12574 11964 11451 11346 11353 10702 10646 10556 10463 10407 10625 10872 10805 10653 10574 10431 10383 10296 10872 10635 10297 10570 10662 10709 10413 10846 10371 9924 9828 9897 9721 10171 10738 10812 10511 10244 10368 10457 10186 10166 10827 10997 10940 10756 10893 10236 9960 10018 10063 10002 9728 10002 10177 9948 9394 9308 9155 9103 9732
Data Y:
57.42 56.12 59.15 63.77 63.96 57.81 55.3 51.8 53.26 53.38 45.85 44.23 40.22 44.61 49.14 42.94 41.84 37.75 35.54 37.13 33.19 32.67 30.52 30.7 29.59 28.76 29.08 26.95 29.58 28.24 27.28 25.48 24.87 29.87 32.33 30.23 27.46 24.46 27.34 28.37 26.09 25.59 24.67 25.61 25.97 24.31 20.36 19.82 19.32 19.2 21.74 26.29 25.9 25.36 27.64 28.57 25.38 25.71 27.6 25.85 26.54
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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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