Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
10519.2 10414.9 12476.8 12384.6 12266.7 12919.9 11497.3 12142 13919.4 12656.8 12034.1 13199.7 10881.3 11301.2 13643.9 12517 13981.1 14275.7 13435 13565.7 16216.3 12970 14079.9 14235 12213.4 12581 14130.4 14210.8 14378.5 13142.8 13714.7 13621.9 15379.8 13306.3 14391.2 14909.9 14025.4 12951.2 14344.3 16093.4 15413.6 14705.7 15972.8 16241.4 16626.4 17136.2 15622.9 18003.9 16136.1 14423.7 16789.4 16782.2 14133.8 12607 12004.5 12175.4 13268 12299.3 11800.6 13873.3 12315
Type of transformation
red
Full Box-Cox transform
Simple Box-Cox transform
Minimum lambda
blue
-2
-8
-7
-6
-5
-4
-3
-2
-1
Maximum lambda
TRUE
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?
ipkl
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
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation