R version 2.6.0 (2007-10-03)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(99,115.4,106.9,107.1,99.3,99.2,108.3,105.6,99.5,107.4,93.1,88.1,110.7,113.1,99.6,93.6,98.6,99.6,114.3,107.8,101.2,112.5,100.5,93.9,116.2,112,106.4,95.7,96,95.8,103,102.2,98.4,111.4,86.6,91.3,107.9,101.8,104.4,93.4,100.1,98.5,112.9,101.4,107.1,110.8,90.3,95.5,111.4,113,107.5,95.9,106.3,105.2,117.2,106.9,108.2,110,96.1,100.6)
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: Wessa P., (2007), Tukey lambda PPCC Plot (v1.0.1) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_tukeylambda.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description
> gp <- function(lambda, p)
+ {
+ (p^lambda-(1-p)^lambda)/lambda
+ }
> sortx <- sort(x)
> c <- array(NA,dim=c(201))
> for (i in 1:201)
+ {
+ if (i != 101) c[i] <- cor(gp(ppoints(x), lambda=(i-101)/100),sortx)
+ }
> postscript(file="/var/www/html/rcomp/tmp/10m091196509473.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot((-100:100)/100,c[1:201],xlab='lambda',ylab='correlation',main='PPCC Plot - Tukey lambda')
> grid()
> dev.off()
null device 
          1 
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Tukey Lambda - Key Values',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Distribution (lambda)',1,TRUE)
> a<-table.element(a,'Correlation',1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Approx. Cauchy (lambda=-1)',header=TRUE)
> a<-table.element(a,c[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Exact Logistic (lambda=0)',header=TRUE)
> a<-table.element(a,(c[100]+c[102])/2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Approx. Normal (lambda=0.14)',header=TRUE)
> a<-table.element(a,c[115])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'U-shaped (lambda=0.5)',header=TRUE)
> a<-table.element(a,c[151])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Exactly Uniform (lambda=1)',header=TRUE)
> a<-table.element(a,c[201])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/2ficj1196509473.tab") 
> 
> system("convert tmp/10m091196509473.ps tmp/10m091196509473.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.684   0.193   0.823