R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(1.73,1.75,1.75,1.75,1.73,1.74,1.75,1.75,1.34,1.24,1.24,1.26,1.25,1.26,1.26,1.22,1.01,1.03,1.01,1.01,1,0.98,1,1.01,1,1,1,1.03,1.26,1.43,1.61,1.76,1.93,2.16,2.28,2.5,2.63,2.79,3,3.04,3.26,3.5,3.62,3.78,4,4.16,4.29,4.49,4.59,4.79,4.94,4.99,5.24,5.25,5.25,5.25,5.25,5.24,5.25,5.26,5.26,5.25,5.25,5.25,5.26,5.02,4.94,4.76,4.49,4.24,3.94,2.98,2.61,2.28,1.98,2,2.01,2,1.81,0.97,0.39,0.16,0.15,0.22)
> par1 = '200'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1)
> if (par1 < 10) par1 = 10
> if (par1 > 5000) par1 = 5000
> library(lattice)
> library(boot)

Attaching package: 'boot'


	The following object(s) are masked from package:lattice :

	 melanoma 

> boot.stat <- function(s,i)
+ {
+ s.mean <- mean(s[i])
+ s.median <- median(s[i])
+ s.midrange <- (max(s[i]) + min(s[i])) / 2
+ c(s.mean, s.median, s.midrange)
+ }
> (r <- boot(x,boot.stat, R=par1, stype='i'))

ORDINARY NONPARAMETRIC BOOTSTRAP


Call:
boot(data = x, statistic = boot.stat, R = par1, stype = "i")


Bootstrap Statistics :
    original     bias    std. error
t1* 2.715595 0.01077738  0.18189387
t2* 2.005000 0.14237500  0.34076840
t3* 2.705000 0.02192500  0.07337465
> postscript(file="/var/www/html/rcomp/tmp/13f5p1244124485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2lp4c1244124485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3607e1244124485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4yv9e1244124485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/5c8sy1244124485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6qyeo1244124485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange')
> dev.off()
null device 
          1 
> z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3]))
> colnames(z) <- list('mean','median','midrange')
> postscript(file="/var/www/html/rcomp/tmp/7vfgh1244124485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
Warning message:
In bxp(list(stats = c(2.30404761904762, 2.60916666666667, 2.71095238095238,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Estimation Results of Bootstrap',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'statistic',header=TRUE)
> a<-table.element(a,'Q1',header=TRUE)
> a<-table.element(a,'Estimate',header=TRUE)
> a<-table.element(a,'Q3',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'IQR',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mean',header=TRUE)
> q1 <- quantile(r$t[,1],0.25)[[1]]
> q3 <- quantile(r$t[,1],0.75)[[1]]
> a<-table.element(a,q1)
> a<-table.element(a,r$t0[1])
> a<-table.element(a,q3)
> a<-table.element(a,sqrt(var(r$t[,1])))
> a<-table.element(a,q3-q1)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'median',header=TRUE)
> q1 <- quantile(r$t[,2],0.25)[[1]]
> q3 <- quantile(r$t[,2],0.75)[[1]]
> a<-table.element(a,q1)
> a<-table.element(a,r$t0[2])
> a<-table.element(a,q3)
> a<-table.element(a,sqrt(var(r$t[,2])))
> a<-table.element(a,q3-q1)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'midrange',header=TRUE)
> q1 <- quantile(r$t[,3],0.25)[[1]]
> q3 <- quantile(r$t[,3],0.75)[[1]]
> a<-table.element(a,q1)
> a<-table.element(a,r$t0[3])
> a<-table.element(a,q3)
> a<-table.element(a,sqrt(var(r$t[,3])))
> a<-table.element(a,q3-q1)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/8m2qg1244124485.tab") 
> 
> system("convert tmp/13f5p1244124485.ps tmp/13f5p1244124485.png")
> system("convert tmp/2lp4c1244124485.ps tmp/2lp4c1244124485.png")
> system("convert tmp/3607e1244124485.ps tmp/3607e1244124485.png")
> system("convert tmp/4yv9e1244124485.ps tmp/4yv9e1244124485.png")
> system("convert tmp/5c8sy1244124485.ps tmp/5c8sy1244124485.png")
> system("convert tmp/6qyeo1244124485.ps tmp/6qyeo1244124485.png")
> system("convert tmp/7vfgh1244124485.ps tmp/7vfgh1244124485.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.821   1.153   2.583