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.

  Natural language support but running in an English locale

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.

> par3 = '20'
> par2 = '2006'
> par1 = '1995'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: Wessa P., (2007), Figure 1 of the paper 'How to Objectively Rate Investment Experts in Absence of Full Disclosure? An Approach Based on a Near Perfect Discrimination Model', Free Statistics Software, Office for Research Development and Education, version 1.0.2, URL http://www.wessa.net/rwasp_QRW1.wasp/
> #Source of accompanying publication: 
> #Technical description: Write here your technical program description (available to developers only).
> par1 <- as.numeric(par1)
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> if (par3 > 50) par3 = 50
> if (par3 < 5) par3 = 5
> load('Q2.RData')
> maxnumsubsets <- 5
> startyear <- par1
> endyear <- par2
> numseries <- 66
> numsim <- par3
> simarr <- array(NA,dim=c(numseries,length(tsarr[1,]),numsim))
> lenser <- array(NA,dim=c(numseries,2,numsim))
> minser <- array(NA,dim=c(numseries,2,numsim))
> maxser <- array(NA,dim=c(numseries,2,numsim))
> medser <- array(NA,dim=c(numseries,2,numsim))
> q1ser <- array(NA,dim=c(numseries,2,numsim))
> q3ser <- array(NA,dim=c(numseries,2,numsim))
> for (i in 1:numseries)
+ {
+ dum <- tsarr[i,!is.na(tsarr[i,])]
+ lenser[i,1,1] <- length(dum)
+ minser[i,1,1] <- min(dum)
+ maxser[i,1,1] <- max(dum)
+ medser[i,1,1] <- median(dum)
+ q1ser[i,1,1] <- quantile(dum,0.25)
+ q3ser[i,1,1] <- quantile(dum,0.75)
+ omean <- mean(tsarr[i,],na.rm=TRUE)
+ osd <- sd(tsarr[i,],na.rm=TRUE)
+ for (jj in 1:numsim)
+ {
+ dum <- rnorm(lenser[i,1,1],omean,osd)
+ for (j in 1:lenser[i,1,1])
+ {
+ simarr[i,j,jj] <- dum[j]
+ }
+ dum <- simarr[i,!is.na(simarr[i,,jj]),jj]
+ lenser[i,2,jj] <- length(dum)
+ minser[i,2,jj] <- min(dum)
+ maxser[i,2,jj] <- max(dum)
+ medser[i,2,jj] <- median(dum)
+ q1ser[i,2,jj] <- quantile(dum,0.25)
+ q3ser[i,2,jj] <- quantile(dum,0.75)
+ }
+ }
> iqr1<-(rep(q3ser[,1,1],numsim)-rep(q1ser[,1,1],numsim))
> iqr2<-(c(q3ser[,2,])-c(q1ser[,2,]))
> postscript(file="/var/www/html/rcomp/tmp/145um1192711552.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow=c(3,3))
> hist(lenser[,1,1],main='',xlab='length of QRW')
> hist(medser[,1,1],main='',xlab='median of QRW')
> hist(maxser[,1,1]-minser[,1,1],main='',xlab='range of QRW')
> hist(minser[,1,1],main='',xlab='min of QRW')
> hist(maxser[,1,1],main='',xlab='max of QRW')
> hist(q3ser[,1,1]-q1ser[,1,1],main='',xlab='IQR of QRW')
> plot(rep(minser[,1,1],numsim),c(minser[,2,]),xlab='min of QRW',ylab='min of RW')
> plot(rep(maxser[,1,1],numsim),c(maxser[,2,]),xlab='max of QRW',ylab='max of RW')
> plot(iqr1,iqr2,xlab='IQR of QRW',ylab='IQR of RW')
> par(op)
> dev.off()
null device 
          1 
> 
> system("convert tmp/145um1192711552.ps tmp/145um1192711552.png")
> 
> 
> proc.time()
   user  system elapsed 
 40.885   0.838  41.179