R version 2.7.1 (2008-06-23)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(81.6,113.8,97.6,120.1,101.9,97.6,150,143.8,103.7,115.3,87.4,97.6,84,96.1,88,120.6,121.1,109.7,149.2,156.5,109.3,102,90,85.9,88.4,88.4,100,120.6,103.3,107.1,168.1,172.1,104.9,112.8,88.8,109,89.5,90.2,91.2,116.9,106.1,106.1,170.4,163.9,108,118.6,94.7,101.4,94.86,101.61,96.04,115.96,123.87,115.59,178.58,184.31,115.59,117.91,95.22,113.49,97.84,97.84,98.82,142.58,122.57,122.29,167.48,176.09,121.78,122.6,107.8,116.77,99.56,103.41,107.77,139.17,130.56,125.18,181.69,194.7,125.18,123.54,112.25,123.21,109.02,115.97,118.71,126.4,129.39,128.97,192.64,188.1,128.03,132.42,114.73,123.82)
> 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* 119.4293  0.2086427    2.812276
t2* 115.0150 -0.6519500    2.665467
t3* 138.1500 -0.1245000    1.826532
> postscript(file="/var/www/html/rcomp/tmp/1zjnj1218471067.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2yoxs1218471067.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/35zpu1218471067.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/49agl1218471067.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/5dfms1218471067.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6yn2s1218471067.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$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$t[,3]))
> colnames(z) <- list('mean','median','midrange')
> postscript(file="/var/www/html/rcomp/tmp/74ec91218471067.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Estimation Results of Bootstrap',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'statistic',header=TRUE)
> a<-table.element(a,'Q1',header=TRUE)
> a<-table.element(a,'Estimate',header=TRUE)
> a<-table.element(a,'Q3',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'IQR',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mean',header=TRUE)
> q1 <- quantile(r$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/8t33i1218471068.tab") 
> 
> system("convert tmp/1zjnj1218471067.ps tmp/1zjnj1218471067.png")
> system("convert tmp/2yoxs1218471067.ps tmp/2yoxs1218471067.png")
> system("convert tmp/35zpu1218471067.ps tmp/35zpu1218471067.png")
> system("convert tmp/49agl1218471067.ps tmp/49agl1218471067.png")
> system("convert tmp/5dfms1218471067.ps tmp/5dfms1218471067.png")
> system("convert tmp/6yn2s1218471067.ps tmp/6yn2s1218471067.png")
> system("convert tmp/74ec91218471067.ps tmp/74ec91218471067.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.013   1.104   2.568