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Data:
63.1 63 74.9 64.7 68.5 73.9 57.3 62.5 75.7 73.5 71 76.1 65 66.3 74.4 71.1 71.9 75.7 64.3 62.6 75.3 80.3 72.2 80.3 71.3 70.7 77.5 79.2 75.4 83.4 72.9 68.4 85 86.2 76.7 91.2 76 77 87.3 83.1 81.1 88.4 76.7 70.9 85.9 84.8 79.6 89.9 74 74.8 91.4 84.1 80 92.2 77.3 78.1 93.6 92.9 89.8 101.8 84.8 90.8 106.8 92.2 101.5 101.6 86 89.7 106.3 107.8 106.7 118.1 100.3 97.5 112.9 101.3 107.8 110.3 94.6 93.9 104.8 109.4 107.6 112.3 99 99.9 111.1 111.2 109.5 111.6 102.2 94.5 114.4 116.8 110.5 121.1 106.3 104.6 117.3 112.4 107.5 116.9 104.9 95.9 121.5 124.1 110.7 128.1 108.9 111.2 131.9 120.5 115.4 130.8 112.6 111.1 129.5 131.8 127.7 142.6 115.8 119.5 139.8 130.6 126.2 141.7 118.9 120.3 141.2 138.9 141.3 153.7 131 136.5 160.1 139.8 143.8
Type of transformation
Full Box-Cox transform
Simple Box-Cox transform
Minimum lambda
-2
-8
-7
-6
-5
-4
-3
-2
-1
Maximum lambda
2
1
2
3
4
5
6
7
8
Constant term to be added before analysis is performed
(?)
Display table with original and transformed data?
No
Yes
Chart options
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(qnorm(ppoints(x), mean=0, sd=1),x1) if (mx < c[i]) { mx <- c[i] mxli <- l[i] } } c mx mxli if (mxli != 0) { x1 <- (x^mxli - 1) / mxli } else { x1 <- log(x) } bitmap(file='test1.png') plot(l,c,main='Box-Cox Normality Plot',xlab='Lambda',ylab='correlation') mtext(paste('Optimal Lambda =',mxli)) grid() dev.off() bitmap(file='test2.png') hist(x,main='Histogram of Original Data',xlab='X',ylab='frequency') grid() dev.off() bitmap(file='test3.png') hist(x1,main='Histogram of Transformed Data',xlab='X',ylab='frequency') grid() dev.off() bitmap(file='test4.png') qqnorm(x) grid() mtext('Original Data') dev.off() bitmap(file='test5.png') qqnorm(x1) grid() mtext('Transformed Data') dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Box-Cox Normality 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',header=TRUE) a<-table.element(a,mxli) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
Compute
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Raw Input
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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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