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Data:
12300.00 12092.80 12380.80 12196.90 9455.00 13168.00 13427.90 11980.50 11884.80 11691.70 12233.80 14341.40 13130.70 12421.10 14285.80 12864.60 11160.20 14316.20 14388.70 14013.90 13419.00 12769.60 13315.50 15332.90 14243.00 13824.40 14962.90 13202.90 12199.00 15508.90 14199.80 15169.60 14058.00 13786.20 14147.90 16541.70 13587.50 15582.40 15802.80 14130.50 12923.20 15612.20 16033.70 16036.60 14037.80 15330.60 15038.30 17401.80 14992.50 16043.70 16929.60 15921.30 14417.20 15961.00 17851.90 16483.90 14215.50 17429.70 17839.50 17629.20
Type of transformation
50
Full Box-Cox transform
Simple Box-Cox transform
Minimum lambda
50
-2
-8
-7
-6
-5
-4
-3
-2
-1
Maximum lambda
Y
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?
uitvoer Vlaanderen
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')
Compute
Summary of computational transaction
Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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