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Data X:
2333.3 2282.2 2458.2 2345.5 2065.2 2332.5 2077.5 1691.4 2381.9 2526 2212.1 2459.9 2178.8 2318.2 2661.8 2407.9 2040.6 2601.6 2106.3 1829.9 2546.1 2363 2435.8 2668 2316.9 2324.2 2610.8 2413.2 2345.2 2590.8 2132.1 1990.7 2641.7 2437.1 2649.2 2819.4 2405.6 2451.3 2878.5 2534.1 2670.6 2909.7 2261.8 2135.3 2870.4 2803.2 2775.1 2633.7 2930.6 2779.7 3039.2 2752.7 2743.1 2914 2711.9 2295.8 2840.6 3230.5 2761.1 2769.6
Data Y:
2894.3 2838.1 3137.7 2703.7 2623.6 2691.1 2577.9 2430.5 2871 2922.5 2810.8 3070.3 2790 2821 3383.6 3038.4 2877.3 3283.7 2927.3 2952.5 3328.9 3467.3 3355.6 3707 3275.6 3466.5 4054.3 3708.5 3339 3559.8 3189.2 3620.7 3915.4 3804.3 4391.6 4975.9 4478.7 4455.8 5661.8 4062.8 4257.7 4114.2 3793.8 4170 4004.9 4129.7 4116 4133.8 4081.2 3854.1 4239.8 3718.5 4183.1 4336.1 4299.2 4285.3 4676.7 4980.6 5207.4 5221.7
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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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