R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(6,6.7,-0.6,5.8,16.4,1.5,5.1,14.7,4.3,1.5,9.1,4.3,5.7,13,14.5,9.7,-4.7,7.3,5.2,-2.5,11.5,4.9,-2.4,-0.3,4.4,7.9,-9.7,-4.1,16.4,-4.9,3.5,3.8,-0.2,3.1,0.7,-2.8,5.9,-5.3,-2.9,6.6,-8.1,1.3,6.9,-7.2,-1.9,4,-5.7,3.9,-7.6,-0.9,7.3,-3.7,-2.5,9.3,1.3,9.5,11.3,-1.7,8,-4.8,1.6,1.9,-0.9,5.5,1.7,-5.4,1.9,0.2,-13.3,-8.2,0.2,5.7,-1.2,-2.8,5.5,-17.3,1.4,-2.2,-8.6,-5,4.1,0.7,-4.2,-2.3,-3.4,-4.2,-14.2,1.6,-4.9,-1.8,-0.5,-2.3,-5.3,-0.2,5.1,-1.5)
> par4 = 'P1 P5 Q1 Q3 P95 P99'
> par3 = '0'
> par2 = '5'
> par1 = '200'
> par4 <- 'P1 P5 Q1 Q3 P95 P99'
> par3 <- '0'
> par2 <- '5'
> par1 <- '200'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 ()
> #Author: root
> #To cite this work: Wessa P., (2013), Bootstrap Plot for Central Tendency (v1.0.13) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_bootstrapplot1.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> 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 P. PONCET.
For a complete list of functions, use 'library(help = "modeest")' or 'help.start()'.

> library(lattice)
> library(boot)

Attaching package: 'boot'

The following object is 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*  1.0958333 -0.02172917   0.6658679
t2*  1.0000000 -0.20475000   0.9256343
t3* -0.4500000  0.66575000   1.0975827
t4*  1.4200000  0.03095000   5.2679299
t5* -0.9249105  1.01131953   2.7984997
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
9: 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/1k64i1429522867.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2x5az1429522867.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/36n9k1429522867.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/432ns1429522867.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/5dbdv1429522867.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,5],type='p',ylab='simulated values',main='Simulation of Mode of Kernel Density')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6tj0l1429522867.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/741ye1429522867.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8x4se1429522867.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9qczq1429522867.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,4],col='black',main='Density Plot',xlab='mode')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/10ea8e1429522867.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$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$t[,5]))
> colnames(z) <- list('mean','median','midrange','mode','mode k.dens')
> postscript(file="/var/wessaorg/rcomp/tmp/111kw11429522867.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
Warning message:
In bxp(list(stats = c(-0.592708333333333, 0.619791666666667, 1.05572916666667,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Estimation Results of Bootstrap',10,TRUE)
> a<-table.row.end(a)
> if (par4 == 'P1 P5 Q1 Q3 P95 P99') {
+ myq.1 <- 0.01
+ myq.2 <- 0.05
+ myq.3 <- 0.95
+ myq.4 <- 0.99
+ myl.1 <- 'P1'
+ myl.2 <- 'P5'
+ myl.3 <- 'P95'
+ myl.4 <- 'P99'
+ }
> if (par4 == 'P0.5 P2.5 Q1 Q3 P97.5 P99.5') {
+ myq.1 <- 0.005
+ myq.2 <- 0.025
+ myq.3 <- 0.975
+ myq.4 <- 0.995
+ myl.1 <- 'P0.5'
+ myl.2 <- 'P2.5'
+ myl.3 <- 'P97.5'
+ myl.4 <- 'P99.5'
+ }
> if (par4 == 'P10 P20 Q1 Q3 P80 P90') {
+ myq.1 <- 0.10
+ myq.2 <- 0.20
+ myq.3 <- 0.80
+ myq.4 <- 0.90
+ myl.1 <- 'P10'
+ myl.2 <- 'P20'
+ myl.3 <- 'P80'
+ myl.4 <- 'P90'
+ }
> a<-table.row.start(a)
> a<-table.element(a,'statistic',header=TRUE)
> a<-table.element(a,myl.1,header=TRUE)
> a<-table.element(a,myl.2,header=TRUE)
> a<-table.element(a,'Q1',header=TRUE)
> a<-table.element(a,'Estimate',header=TRUE)
> a<-table.element(a,'Q3',header=TRUE)
> a<-table.element(a,myl.3,header=TRUE)
> a<-table.element(a,myl.4,header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'IQR',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mean',header=TRUE)
> q1 <- quantile(r$t[,1],0.25)[[1]]
> q3 <- quantile(r$t[,1],0.75)[[1]]
> p01 <- quantile(r$t[,1],myq.1)[[1]]
> p05 <- quantile(r$t[,1],myq.2)[[1]]
> p95 <- quantile(r$t[,1],myq.3)[[1]]
> p99 <- quantile(r$t[,1],myq.4)[[1]]
> a<-table.element(a,signif(p01,par2))
> a<-table.element(a,signif(p05,par2))
> a<-table.element(a,signif(q1,par2))
> a<-table.element(a,signif(r$t0[1],par2))
> a<-table.element(a,signif(q3,par2))
> a<-table.element(a,signif(p95,par2))
> a<-table.element(a,signif(p99,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$t[,2],0.75)[[1]]
> p01 <- quantile(r$t[,2],myq.1)[[1]]
> p05 <- quantile(r$t[,2],myq.2)[[1]]
> p95 <- quantile(r$t[,2],myq.3)[[1]]
> p99 <- quantile(r$t[,2],myq.4)[[1]]
> a<-table.element(a,signif(p01,par2))
> a<-table.element(a,signif(p05,par2))
> a<-table.element(a,signif(q1,par2))
> a<-table.element(a,signif(r$t0[2],par2))
> a<-table.element(a,signif(q3,par2))
> a<-table.element(a,signif(p95,par2))
> a<-table.element(a,signif(p99,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$t[,3],0.75)[[1]]
> p01 <- quantile(r$t[,3],myq.1)[[1]]
> p05 <- quantile(r$t[,3],myq.2)[[1]]
> p95 <- quantile(r$t[,3],myq.3)[[1]]
> p99 <- quantile(r$t[,3],myq.4)[[1]]
> a<-table.element(a,signif(p01,par2))
> a<-table.element(a,signif(p05,par2))
> a<-table.element(a,signif(q1,par2))
> a<-table.element(a,signif(r$t0[3],par2))
> a<-table.element(a,signif(q3,par2))
> a<-table.element(a,signif(p95,par2))
> a<-table.element(a,signif(p99,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$t[,4],0.75)[[1]]
> p01 <- quantile(r$t[,4],myq.1)[[1]]
> p05 <- quantile(r$t[,4],myq.2)[[1]]
> p95 <- quantile(r$t[,4],myq.3)[[1]]
> p99 <- quantile(r$t[,4],myq.4)[[1]]
> a<-table.element(a,signif(p01,par2))
> a<-table.element(a,signif(p05,par2))
> a<-table.element(a,signif(q1,par2))
> a<-table.element(a,signif(r$t0[4],par2))
> a<-table.element(a,signif(q3,par2))
> a<-table.element(a,signif(p95,par2))
> a<-table.element(a,signif(p99,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$t[,5],0.75)[[1]]
> p01 <- quantile(r$t[,5],myq.1)[[1]]
> p05 <- quantile(r$t[,5],myq.2)[[1]]
> p95 <- quantile(r$t[,5],myq.3)[[1]]
> p99 <- quantile(r$t[,5],myq.4)[[1]]
> a<-table.element(a,signif(p01,par2))
> a<-table.element(a,signif(p05,par2))
> a<-table.element(a,signif(q1,par2))
> a<-table.element(a,signif(r$t0[5],par2))
> a<-table.element(a,signif(q3,par2))
> a<-table.element(a,signif(p95,par2))
> a<-table.element(a,signif(p99,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/12e0991429522867.tab") 
> 
> try(system("convert tmp/1k64i1429522867.ps tmp/1k64i1429522867.png",intern=TRUE))
character(0)
> try(system("convert tmp/2x5az1429522867.ps tmp/2x5az1429522867.png",intern=TRUE))
character(0)
> try(system("convert tmp/36n9k1429522867.ps tmp/36n9k1429522867.png",intern=TRUE))
character(0)
> try(system("convert tmp/432ns1429522867.ps tmp/432ns1429522867.png",intern=TRUE))
character(0)
> try(system("convert tmp/5dbdv1429522867.ps tmp/5dbdv1429522867.png",intern=TRUE))
character(0)
> try(system("convert tmp/6tj0l1429522867.ps tmp/6tj0l1429522867.png",intern=TRUE))
character(0)
> try(system("convert tmp/741ye1429522867.ps tmp/741ye1429522867.png",intern=TRUE))
character(0)
> try(system("convert tmp/8x4se1429522867.ps tmp/8x4se1429522867.png",intern=TRUE))
character(0)
> try(system("convert tmp/9qczq1429522867.ps tmp/9qczq1429522867.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ea8e1429522867.ps tmp/10ea8e1429522867.png",intern=TRUE))
character(0)
> try(system("convert tmp/111kw11429522867.ps tmp/111kw11429522867.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  5.109   0.682   5.840