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Data:
1.9 3 6 6.2 6.7 7 7.1 7.9 8 8 8.2 8.4 8.5 8.5 8.6 8.8 8.8 8.9 9 9 9 9.2 9.3 9.3 9.4 9.4 9.5 9.6 9.8 9.8 9.9 10 10 10.1 10.1 10.1 10.2 10.2 10.3 10.3 10.4 10.5 10.5 10.5 10.5 10.6 10.6 10.6 10.7 10.8 10.8 10.8 10.9 11 11.1 11.1 11.1 11.1 11.3 11.3 11.3 11.4 11.4 11.5 11.7 11.8 11.8 11.8 11.9 12 12 12 12.1 12.2 12.2 12.3 12.3 12.4 12.6 12.7 12.7 12.7 12.8 12.8 13 13.1 13.1 13.2 13.3 13.3 13.3 13.4 13.4 13.6 13.6 13.7 13.7 13.7 13.8 13.8 14.2 14.3 14.5 14.5 14.5 14.6 14.7 14.7 14.8 14.8 14.9 15.1 15.2 15.2 15.4 15.7 15.8 15.8 15.9 16 16 16.2 16.3 16.4 16.4 16.4 16.4 16.7 16.8 17.2 17.3 17.3 17.6 17.6 17.6 18 18.5 18.5 18.6 18.7 18.8 18.8 19 19.5 19.6 19.8 19.9 20.7 20.8 21 21 21.1 21.2 21.8 21.9 21.9 21.9 22.2 22.6 22.8 23.2 23.5 23.5 23.5 23.7 24.3 24.8 24.9 24.9 26.1 26.2 26.8
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')
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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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