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(435,431,434,439,455,452,426,428,433,438,442,446,442,436,444,454,469,471,443,437,444,451,457,460,454,439,441,446,459,456,433,424,430,428,424,419,409,397,397,401,413,413,390,385,397,398,406,412,409,404,412,418,434,431,406,416,424,427,438,444,442,443,453,471,476,476,461,462,460,463,467,468,465,459,465,471,472,472,456,455,456,462,463,461)
> 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* 439.2857  0.4845238    2.460025
t2* 442.0000 -0.4800000    2.768187
t3* 430.5000  1.5200000    2.529338
t4* 439.0000  4.3566667   18.525149
t5* 449.1228  1.5496363   11.046946
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
8: 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/1lt6u1353679226.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2ky241353679226.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3ibb41353679226.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/41krr1353679226.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/5gijp1353679226.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,5],type='p',ylab='simulated values',main='Simulation of Mode of Kernel Density')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6kbrj1353679226.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7wts21353679226.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8np321353679226.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9pgg01353679226.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,4],col='black',main='Density Plot',xlab='mode')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/10h2fg1353679226.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$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$t[,5]))
> colnames(z) <- list('mean','median','midrange','mode','mode k.dens')
> postscript(file="/var/wessaorg/rcomp/tmp/115nd21353679226.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
Warning message:
In bxp(list(stats = c(434.75, 437.72619047619, 440.172619047619,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Estimation Results of Bootstrap',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'statistic',header=TRUE)
> a<-table.element(a,'Q1',header=TRUE)
> a<-table.element(a,'Estimate',header=TRUE)
> a<-table.element(a,'Q3',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'IQR',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mean',header=TRUE)
> q1 <- quantile(r$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/12em0q1353679226.tab") 
> 
> try(system("convert tmp/1lt6u1353679226.ps tmp/1lt6u1353679226.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ky241353679226.ps tmp/2ky241353679226.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ibb41353679226.ps tmp/3ibb41353679226.png",intern=TRUE))
character(0)
> try(system("convert tmp/41krr1353679226.ps tmp/41krr1353679226.png",intern=TRUE))
character(0)
> try(system("convert tmp/5gijp1353679226.ps tmp/5gijp1353679226.png",intern=TRUE))
character(0)
> try(system("convert tmp/6kbrj1353679226.ps tmp/6kbrj1353679226.png",intern=TRUE))
character(0)
> try(system("convert tmp/7wts21353679226.ps tmp/7wts21353679226.png",intern=TRUE))
character(0)
> try(system("convert tmp/8np321353679226.ps tmp/8np321353679226.png",intern=TRUE))
character(0)
> try(system("convert tmp/9pgg01353679226.ps tmp/9pgg01353679226.png",intern=TRUE))
character(0)
> try(system("convert tmp/10h2fg1353679226.ps tmp/10h2fg1353679226.png",intern=TRUE))
character(0)
> try(system("convert tmp/115nd21353679226.ps tmp/115nd21353679226.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  8.617   1.174   9.790