R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(93.61,93.17,91.60,90.30,90.88,91.06,92.05,95.29,96.44,96.49,96.52,96.09,99.16,98.09,99.41,99.87,100.06,99.65,99.92,98.44,102.64,112.33,115.63,118.29,121.43,129.96,147.73,154.10,150.09,144.14,141.54,136.68,129.32,118.99,109.61,106.22,104.97,102.45,101.91,101.77,102.67,103.45,101.41,102.45,102.17,101.40,101.68,100.61,97.93,98.30,99.79,101.62,101.55,102.43,102.09,102.01,102.26,101.24,100.91,100.67,100.33,99.99,99.23,98.17,97.38,96.70,98.65,100.68,101.07,101.12,101.13,99.88,99.20,99.91,103.62,108.05,113.96,117.39,126.04,139.67,145.04,142.37,137.72,132.46)
> par4 = 'P1 P5 Q1 Q3 P95 P99'
> par3 = '0'
> par2 = '5'
> par1 = '50'
> par4 <- 'P1 P5 Q1 Q3 P95 P99'
> par3 <- '0'
> par2 <- '5'
> par1 <- '50'
> #'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* 107.7893  0.21691905   1.6787295
t2* 101.4050  0.03150000   0.4265694
t3* 122.2000 -0.57680000   1.4308185
t4* 102.4500  1.76460476  10.6511602
t5* 100.8812  0.04007682   0.4589806
Warning message:
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/fisher/rcomp/tmp/1p5y61389310764.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/2b55o1389310764.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/3ooko1389310764.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/44gcl1389310764.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/5gd831389310764.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,5],type='p',ylab='simulated values',main='Simulation of Mode of Kernel Density')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/67qr41389310764.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/7d9jd1389310764.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/8821o1389310764.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/9fpru1389310764.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,4],col='black',main='Density Plot',xlab='mode')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/10o49k1389310764.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$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$t[,5]))
> colnames(z) <- list('mean','median','midrange','mode','mode k.dens')
> postscript(file="/var/fisher/rcomp/tmp/11u3lt1389310764.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
Warning message:
In bxp(list(stats = c(103.879880952381, 106.882738095238, 107.968392857143,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Estimation Results of Bootstrap',10,TRUE)
> a<-table.row.end(a)
> if (par4 == 'P1 P5 Q1 Q3 P95 P99') {
+ myq.1 <- 0.01
+ myq.2 <- 0.05
+ myq.3 <- 0.95
+ myq.4 <- 0.99
+ myl.1 <- 'P1'
+ myl.2 <- 'P5'
+ myl.3 <- 'P95'
+ myl.4 <- 'P99'
+ }
> if (par4 == 'P0.5 P2.5 Q1 Q3 P97.5 P99.5') {
+ myq.1 <- 0.005
+ myq.2 <- 0.025
+ myq.3 <- 0.975
+ myq.4 <- 0.995
+ myl.1 <- 'P0.5'
+ myl.2 <- 'P2.5'
+ myl.3 <- 'P97.5'
+ myl.4 <- 'P99.5'
+ }
> if (par4 == 'P10 P20 Q1 Q3 P80 P90') {
+ myq.1 <- 0.10
+ myq.2 <- 0.20
+ myq.3 <- 0.80
+ myq.4 <- 0.90
+ myl.1 <- 'P10'
+ myl.2 <- 'P20'
+ myl.3 <- 'P80'
+ myl.4 <- 'P90'
+ }
> a<-table.row.start(a)
> a<-table.element(a,'statistic',header=TRUE)
> a<-table.element(a,myl.1,header=TRUE)
> a<-table.element(a,myl.2,header=TRUE)
> a<-table.element(a,'Q1',header=TRUE)
> a<-table.element(a,'Estimate',header=TRUE)
> a<-table.element(a,'Q3',header=TRUE)
> a<-table.element(a,myl.3,header=TRUE)
> a<-table.element(a,myl.4,header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'IQR',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mean',header=TRUE)
> q1 <- quantile(r$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/fisher/rcomp/tmp/12xlwc1389310765.tab") 
> 
> try(system("convert tmp/1p5y61389310764.ps tmp/1p5y61389310764.png",intern=TRUE))
character(0)
> try(system("convert tmp/2b55o1389310764.ps tmp/2b55o1389310764.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ooko1389310764.ps tmp/3ooko1389310764.png",intern=TRUE))
character(0)
> try(system("convert tmp/44gcl1389310764.ps tmp/44gcl1389310764.png",intern=TRUE))
character(0)
> try(system("convert tmp/5gd831389310764.ps tmp/5gd831389310764.png",intern=TRUE))
character(0)
> try(system("convert tmp/67qr41389310764.ps tmp/67qr41389310764.png",intern=TRUE))
character(0)
> try(system("convert tmp/7d9jd1389310764.ps tmp/7d9jd1389310764.png",intern=TRUE))
character(0)
> try(system("convert tmp/8821o1389310764.ps tmp/8821o1389310764.png",intern=TRUE))
character(0)
> try(system("convert tmp/9fpru1389310764.ps tmp/9fpru1389310764.png",intern=TRUE))
character(0)
> try(system("convert tmp/10o49k1389310764.ps tmp/10o49k1389310764.png",intern=TRUE))
character(0)
> try(system("convert tmp/11u3lt1389310764.ps tmp/11u3lt1389310764.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  6.265   1.109   7.409