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Data:
3202.1 3650.2 2805.1 3957.5 3941.3 3905.4 3546.9 3208.7 3402 3661.1 3073.9 3419.2 3532.8 3693.1 2622.9 3130.8 3487.5 3349.7 3044.2 3266 3351.5 3606.8 3419.5 3829.5 3505.1 3845.3 2566.6 3658.5 3954 3460.1 3454.1 3412.8 3418 3349.5 3423.4 3242.8 3277.2 3833 2606.3 3643.8 3686.4 3281.6 3669.3 3191.5 3512.7 3970.7 3601.2 3610 4172.1 3956.2 3142.7 3884.3 3892.2 3613 3730.5 3481.3 3649.5 4215.2 4066.6 4196.8 4536.6 4441.6 3548.3 4735.9 4130.6 4356.2 4159.6 3988 4167.8 4902.2 3909.4 4697.6 4308.9 4420.4 3544.2 4433 4479.7 4533.2 4237.5 4207.4 4394 5148.4 4202.2 4682.5 4884.3 5288.9 4505.2 4611.5 5081.1 4523.1 4412.8 4647.4 4778.6 4495.3 4633.5 4360.5 4517.9
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) qqline(x) grid() mtext('Original Data') dev.off() bitmap(file='test5.png') qqnorm(x1) qqline(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 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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