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Data:
100.00 102.83 109.50 115.91 107.94 110.86 118.89 123.38 113.33 116.38 122.04 125.47 115.62 117.91 122.40 125.05 114.18 114.74 120.63 123.68 112.84 115.64 122.32 124.59 116.33 117.45 125.64 128.38 119.87 121.22 128.98 131.35 121.35 123.72 131.06 134.55 125.93 128.90 136.19 140.34 130.48 134.68 141.05 145.44 136.21 139.85 147.13 151.44 143.62 148.55 153.54 159.79 152.55 155.84 160.38 164.22 156.40 160.05 165.60 171.15 161.90 167.21 171.34 176.83 166.27 172.30 176.71 182.99 172.07 178.17 182.20 188.49 176.88 182.13 185.32 192.86 180.27 184.92 187.82 194.94 184.36 188.80 193.42 199.76 188.78 191.49 194.87 198.28 183.24 204.87
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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