R version 2.7.2 (2008-08-25)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(572.775,574.205,579.799,590.072,593.408,597.141,595.404,612.117,628.232,628.884,620.735,569.028,567.456,573.100,584.428,589.379,590.865,595.454,594.167,611.324,612.613,610.763,593.530,542.722,536.662,543.599,555.332,560.854,562.325,554.788,547.344,565.464,577.992,579.714,569.323,506.971,500.857,509.127,509.933,517.009,519.164,512.238,509.239,518.585,522.975,525.192,516.847,455.626,454.724,461.251,470.439,474.605,476.049,471.067,470.984,502.831,512.927,509.673,484.015,431.328,436.087)
> #'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/145g91225037559.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 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> 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/2khqf1225037559.tab") 
> 
> system("convert tmp/145g91225037559.ps tmp/145g91225037559.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.641   0.177   3.044