R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(1.01,1.02,1.04,1.06,1.06,1.06,1.06,1.06,1.02,0.98,0.99,0.99,0.94,0.96,0.98,1.01,1.01,1.02,1.04,1.03,1.05,1.08,1.17,1.11,1.11,1.11,1.2,1.21,1.31,1.37,1.37,1.26,1.23,1.17,1.06,0.95,0.92,0.92,0.9,0.93,0.93,0.97,0.96,0.99,0.98,0.96,1,0.99,1.03,1.02,1.07,1.13,1.15,1.16,1.14,1.15,1.15,1.16,1.17,1.22,1.26,1.29,1.36,1.38,1.37,1.37,1.37,1.36,1.38,1.4,1.44,1.42)
> par3 = '0'
> par2 = '5'
> par1 = '200'
> par3 <- '0'
> par2 <- '5'
> par1 <- '50'
> par1 <- as.numeric(par1)
> par2 <- as.numeric(par2)
> if (par3 == '0') bw <- NULL
> if (par3 != '0') bw <- as.numeric(par3)
> if (par1 < 10) par1 = 10
> if (par1 > 5000) par1 = 5000
> library(modeest)

This is package 'modeest' written by Paul PONCET.
For a complete list of functions, use 'library(help = "modeest")' or 'help.start()'.

> 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
+ s.mode <- mlv(s[i], method='mfv')$M
+ s.kernelmode <- mlv(s[i], method='kernel', bw=bw)$M
+ c(s.mean, s.median, s.midrange, s.mode, s.kernelmode)
+ }
> (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* 1.118056 -0.002013889  0.01647562
t2* 1.060000  0.010700000  0.02725559
t3* 1.170000 -0.002500000  0.01050996
t4* 1.060000  0.039616667  0.11633739
t5* 1.012695  0.006062091  0.03029403
Warning messages:
1: In .deal.ties(ny, i, tie.action, tie.limit) :
  encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit'
the distribution could be multimodal
2: In .deal.ties(ny, i, tie.action, tie.limit) :
  encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit'
the distribution could be multimodal
3: In .deal.ties(ny, i, tie.action, tie.limit) :
  encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit'
the distribution could be multimodal
4: In .deal.ties(ny, i, tie.action, tie.limit) :
  encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit'
the distribution could be multimodal
5: In .deal.ties(ny, i, tie.action, tie.limit) :
  encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit'
the distribution could be multimodal
6: In .deal.ties(ny, i, tie.action, tie.limit) :
  encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit'
the distribution could be multimodal
7: In .deal.ties(ny, i, tie.action, tie.limit) :
  encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit'
the distribution could be multimodal
> postscript(file="/var/wessaorg/rcomp/tmp/1fidy1358300720.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2gpdt1358300720.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/33u2g1358300720.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4p35u1358300720.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/5anb91358300720.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,5],type='p',ylab='simulated values',main='Simulation of Mode of Kernel Density')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6hivw1358300720.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7zqou1358300720.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8kwna1358300720.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9ix7r1358300720.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,4],col='black',main='Density Plot',xlab='mode')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/108wa11358300720.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,5],col='black',main='Density Plot',xlab='mode of kernel dens.')
> dev.off()
null device 
          1 
> z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3],r$t[,4],r$t[,5]))
> colnames(z) <- list('mean','median','midrange','mode','mode k.dens')
> postscript(file="/var/wessaorg/rcomp/tmp/11428i1358300720.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
Warning message:
In bxp(list(stats = c(1.07736111111111, 1.10736111111111, 1.1175,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Estimation Results of Bootstrap',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'statistic',header=TRUE)
> a<-table.element(a,'Q1',header=TRUE)
> a<-table.element(a,'Estimate',header=TRUE)
> a<-table.element(a,'Q3',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'IQR',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mean',header=TRUE)
> q1 <- quantile(r$t[,1],0.25)[[1]]
> q3 <- quantile(r$t[,1],0.75)[[1]]
> a<-table.element(a,signif(q1,par2))
> a<-table.element(a,signif(r$t0[1],par2))
> a<-table.element(a,signif(q3,par2))
> a<-table.element( a,signif( sqrt(var(r$t[,1])),par2 ) )
> a<-table.element(a,signif(q3-q1,par2))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'median',header=TRUE)
> q1 <- quantile(r$t[,2],0.25)[[1]]
> q3 <- quantile(r$t[,2],0.75)[[1]]
> a<-table.element(a,signif(q1,par2))
> a<-table.element(a,signif(r$t0[2],par2))
> a<-table.element(a,signif(q3,par2))
> a<-table.element(a,signif(sqrt(var(r$t[,2])),par2))
> a<-table.element(a,signif(q3-q1,par2))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'midrange',header=TRUE)
> q1 <- quantile(r$t[,3],0.25)[[1]]
> q3 <- quantile(r$t[,3],0.75)[[1]]
> a<-table.element(a,signif(q1,par2))
> a<-table.element(a,signif(r$t0[3],par2))
> a<-table.element(a,signif(q3,par2))
> a<-table.element(a,signif(sqrt(var(r$t[,3])),par2))
> a<-table.element(a,signif(q3-q1,par2))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mode',header=TRUE)
> q1 <- quantile(r$t[,4],0.25)[[1]]
> q3 <- quantile(r$t[,4],0.75)[[1]]
> a<-table.element(a,signif(q1,par2))
> a<-table.element(a,signif(r$t0[4],par2))
> a<-table.element(a,signif(q3,par2))
> a<-table.element(a,signif(sqrt(var(r$t[,4])),par2))
> a<-table.element(a,signif(q3-q1,par2))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mode k.dens',header=TRUE)
> q1 <- quantile(r$t[,5],0.25)[[1]]
> q3 <- quantile(r$t[,5],0.75)[[1]]
> a<-table.element(a,signif(q1,par2))
> a<-table.element(a,signif(r$t0[5],par2))
> a<-table.element(a,signif(q3,par2))
> a<-table.element(a,signif(sqrt(var(r$t[,5])),par2))
> a<-table.element(a,signif(q3-q1,par2))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/124m4y1358300720.tab") 
> 
> try(system("convert tmp/1fidy1358300720.ps tmp/1fidy1358300720.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gpdt1358300720.ps tmp/2gpdt1358300720.png",intern=TRUE))
character(0)
> try(system("convert tmp/33u2g1358300720.ps tmp/33u2g1358300720.png",intern=TRUE))
character(0)
> try(system("convert tmp/4p35u1358300720.ps tmp/4p35u1358300720.png",intern=TRUE))
character(0)
> try(system("convert tmp/5anb91358300720.ps tmp/5anb91358300720.png",intern=TRUE))
character(0)
> try(system("convert tmp/6hivw1358300720.ps tmp/6hivw1358300720.png",intern=TRUE))
character(0)
> try(system("convert tmp/7zqou1358300720.ps tmp/7zqou1358300720.png",intern=TRUE))
character(0)
> try(system("convert tmp/8kwna1358300720.ps tmp/8kwna1358300720.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ix7r1358300720.ps tmp/9ix7r1358300720.png",intern=TRUE))
character(0)
> try(system("convert tmp/108wa11358300720.ps tmp/108wa11358300720.png",intern=TRUE))
character(0)
> try(system("convert tmp/11428i1358300720.ps tmp/11428i1358300720.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  7.229   1.002   8.265