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Data:
90.2 90 88.8 85.8 84.2 80 77.8 76.8 86.4 89.2 86.2 84.6 83.2 83.2 82.6 79.8 77.2 74.8 73 73 83.6 85.6 84.8 84.2 83.4 84.6 84.6 83.8 81.2 79.6 78 78.2 88.8 92 91 91.2 90.4 91.8 92.2 90.2 88.6 87.8 86 87.2 97.6 101.2 100.4 100.2 100.2 103 104.2 104 102.4 101.8 101 102.2 114 118.4 118.8 117.2 117.2 118.4 118.8 117.2 114.4 112.6 111 110.8 120.2 124.4 123.4 121.2 119 119.8 120 118.4 115 113.4 111 111 121.6 126.2 125.8 124.8 122 123.2 124.2 120.8 116.8 114.8 111 109 119.8 124 121.6 118 115.8 116 115.8 114.4 112 110.2 107.4 108.2 117.6 121.4 119.8 115.6 112.6 113.2 112.2 110.8 108 105.2 102.4 101 110.8 116.8 113.8 108 104.4 105.2 105.4 103.2 100.6 97.8 95.8 95 104.8 110.4 106.4 102.2 98.4 98.4 98.6 96.2 92.4 91.4 88.4 87.8 97.6 104.2 100.2 97 92.8 92 93.4 92 89.6 88.6 87.2 86.2 96.8 102 102.6 100.6 94.2 94.2 95.2 95 94 92.2 91 91.2 103.4 105 104.6 103.8 101.8 102.4 103.8 103.4 102 101.8 100.2 101.4 113.8 116 115.6 113 109.4 111 112.4 112.2 111 108.8 107.4 108.6 118.8 122.2 122.6 122.2 118.8 119 118.2 117.8 116.8 114.6 113.4 113.8 124.2 125.8 125.6 122.4 119 119.4 118.6 118 116 114.8 114.6 114.6 124 125.2 124 117.6 113.2 111.4 112.2 109.8 106.4 105.2 102.2 99.8 111 113 108.4 105.4 102 102.8 103.4 101.6 98.6 98 93.8 95.6 105.6 106.8 103.6 101.2 100.4 103.2 105.6 106.6 107.2 107.4 104.8 107.2 117.4 119.4 116.2 112.8 111.6
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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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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