R version 3.2.5 (2016-04-14) -- "Very, Very Secure Dishes"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(84.51,84.54,84.27,84.47,84.25,84.33,84.29,84.53,84.01,84.18,84.08,83.44,83.61,83.89,83.4,82.96,82.76,83.35,87.78,88.99,88.92,88.91,89.79,90.54,93.15,92.79,93.21,95.35,100.91,103.69,104.04,104.16,104.71,105.18,104.92,104.83,104.9,105.05,104.6,103.21,102.52,101.09,101.19,102.34,102.62,102.47,101.82,101.86,101.54,101.98,101.23,100.4,99.94,99.94,100,98.8,99.07,99.46,99.18,98.47,97.12,96.91,96.09,97.17,96.8,97.13,99.9,100.56,100.84,99.81,100.44,100.07,101.32,103.98,104.81,106.23,106.48,107.59,107.16,107.54,107.1,106.38,106.64,106.13)
> par4 = 'P1 P5 Q1 Q3 P95 P99'
> par3 = '0'
> par2 = '5'
> par1 = '750'
> par4 <- 'P1 P5 Q1 Q3 P95 P99'
> par3 <- '0'
> par2 <- '5'
> par1 <- '750'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Wed, 25 Nov 2015 11:13:57 +0000)
> #Author: root
> #To cite this work: Wessa P., (2015), Bootstrap Plot for Central Tendency (v1.0.14) 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)
+ }
> x<-na.omit(x)
> (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*  96.91214 -0.03379460   0.8665478
t2*  99.94000 -0.13118667   0.7951772
t3*  95.17500  0.02770667   0.1488541
t4*  99.94000 -2.98247819   6.3716736
t5* 100.95528  0.59233565   1.6937586
> postscript(file="/var/wessaorg/rcomp/tmp/1bao91462295999.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2o5vp1462295999.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/334sn1462295999.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4zgm51462295999.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/51w8l1462295999.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(r$t[,5],type='p',ylab='simulated values',main='Simulation of Mode of Kernel Density')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/68t8q1462295999.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7vy641462295999.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8477w1462295999.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9obkm1462295999.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$t[,4],col='black',main='Density Plot',xlab='mode')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/10lmym1462295999.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> densityplot(~r$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$t[,5]))
> colnames(z) <- list('mean','median','midrange','mode','mode k.dens')
> postscript(file="/var/wessaorg/rcomp/tmp/11zfjv1462295999.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Estimation Results of Bootstrap',10,TRUE)
> a<-table.row.end(a)
> if (par4 == 'P1 P5 Q1 Q3 P95 P99') {
+ myq.1 <- 0.01
+ myq.2 <- 0.05
+ myq.3 <- 0.95
+ myq.4 <- 0.99
+ myl.1 <- 'P1'
+ myl.2 <- 'P5'
+ myl.3 <- 'P95'
+ myl.4 <- 'P99'
+ }
> if (par4 == 'P0.5 P2.5 Q1 Q3 P97.5 P99.5') {
+ myq.1 <- 0.005
+ myq.2 <- 0.025
+ myq.3 <- 0.975
+ myq.4 <- 0.995
+ myl.1 <- 'P0.5'
+ myl.2 <- 'P2.5'
+ myl.3 <- 'P97.5'
+ myl.4 <- 'P99.5'
+ }
> if (par4 == 'P10 P20 Q1 Q3 P80 P90') {
+ myq.1 <- 0.10
+ myq.2 <- 0.20
+ myq.3 <- 0.80
+ myq.4 <- 0.90
+ myl.1 <- 'P10'
+ myl.2 <- 'P20'
+ myl.3 <- 'P80'
+ myl.4 <- 'P90'
+ }
> a<-table.row.start(a)
> a<-table.element(a,'statistic',header=TRUE)
> a<-table.element(a,myl.1,header=TRUE)
> a<-table.element(a,myl.2,header=TRUE)
> a<-table.element(a,'Q1',header=TRUE)
> a<-table.element(a,'Estimate',header=TRUE)
> a<-table.element(a,'Q3',header=TRUE)
> a<-table.element(a,myl.3,header=TRUE)
> a<-table.element(a,myl.4,header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'IQR',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'mean',header=TRUE)
> q1 <- quantile(r$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/12yb8p1462295999.tab") 
> 
> try(system("convert tmp/1bao91462295999.ps tmp/1bao91462295999.png",intern=TRUE))
character(0)
> try(system("convert tmp/2o5vp1462295999.ps tmp/2o5vp1462295999.png",intern=TRUE))
character(0)
> try(system("convert tmp/334sn1462295999.ps tmp/334sn1462295999.png",intern=TRUE))
character(0)
> try(system("convert tmp/4zgm51462295999.ps tmp/4zgm51462295999.png",intern=TRUE))
character(0)
> try(system("convert tmp/51w8l1462295999.ps tmp/51w8l1462295999.png",intern=TRUE))
character(0)
> try(system("convert tmp/68t8q1462295999.ps tmp/68t8q1462295999.png",intern=TRUE))
character(0)
> try(system("convert tmp/7vy641462295999.ps tmp/7vy641462295999.png",intern=TRUE))
character(0)
> try(system("convert tmp/8477w1462295999.ps tmp/8477w1462295999.png",intern=TRUE))
character(0)
> try(system("convert tmp/9obkm1462295999.ps tmp/9obkm1462295999.png",intern=TRUE))
character(0)
> try(system("convert tmp/10lmym1462295999.ps tmp/10lmym1462295999.png",intern=TRUE))
character(0)
> try(system("convert tmp/11zfjv1462295999.ps tmp/11zfjv1462295999.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  7.799   0.908   8.755