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Type 'q()' to quit R. > x <- c(20.7,20.4,20.3,20.4,19.8,19.5,23.1,23.5,23.5,22.9,21.9,21.5,20.5,20.2,19.4,19.2,18.8,18.8,22.6,23.3,23,21.4,19.9,18.8,18.6,18.4,18.6,19.9,19.2,18.4,21.1,20.5,19.1,18.1,17,17.1,17.4,16.8,15.3,14.3,13.4,15.3,22.1,23.7,22.2,19.5,16.6,17.3,19.8,21.2,21.5,20.6,19.1,19.6,23.4,24.3,24.1,22.8,22.5,23.8,24.9,25.2,24.3,22.8,20.7,19.8,22.5,22.6,22.5,21.8,21.2,20.6,19.9,18.7,17.6,16.4,15.9,16.8,22.8,24,22.2,17.9,16,16) > par3 = '0' > par2 = '5' > par1 = '50' > par3 <- '0' > par2 <- '5' > par1 <- '50' > #'GNU S' R Code compiled by R2WASP v. 1.2.291 () > #Author: root > #To cite this work: Wessa P., (2012), Bootstrap Plot for Central Tendency (v1.0.10) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_bootstrapplot1.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > # > par1 <- as.numeric(par1) > par2 <- as.numeric(par2) > if (par3 == '0') bw <- NULL > if (par3 != '0') bw <- as.numeric(par3) > if (par1 < 10) par1 = 10 > if (par1 > 5000) par1 = 5000 > library(modeest) This is package 'modeest' written by Paul PONCET. For a complete list of functions, use 'library(help = "modeest")' or 'help.start()'. > library(lattice) > library(boot) Attaching package: 'boot' The following object(s) are masked from 'package:lattice': melanoma > boot.stat <- function(s,i) + { + s.mean <- mean(s[i]) + s.median <- median(s[i]) + s.midrange <- (max(s[i]) + min(s[i])) / 2 + s.mode <- mlv(s[i], method='mfv')$M + s.kernelmode <- mlv(s[i], method='kernel', bw=bw)$M + c(s.mean, s.median, s.midrange, s.mode, s.kernelmode) + } > (r <- boot(x,boot.stat, R=par1, stype='i')) ORDINARY NONPARAMETRIC BOOTSTRAP Call: boot(data = x, statistic = boot.stat, R = par1, stype = "i") Bootstrap Statistics : original bias std. error t1* 20.22738 -0.06935714 0.2839270 t2* 20.35000 -0.12000000 0.3629527 t3* 19.30000 0.12100000 0.4633606 t4* 20.76000 -0.50340000 1.8584242 t5* 20.02014 0.40234881 1.1069876 Warning messages: 1: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 2: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 3: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 4: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 5: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 6: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 7: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal > postscript(file="/var/wessaorg/rcomp/tmp/15xjf1353406993.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/22e3t1353406993.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/318sf1353406993.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4tc1h1353406993.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5z0tx1353406993.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$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/6mfbb1353406993.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/7fkgj1353406993.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8w3u71353406993.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9jqqm1353406993.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,4],col='black',main='Density Plot',xlab='mode') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/10tkfg1353406993.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/118sxx1353406993.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',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/12eova1353406993.tab") > > try(system("convert tmp/15xjf1353406993.ps tmp/15xjf1353406993.png",intern=TRUE)) character(0) > try(system("convert tmp/22e3t1353406993.ps tmp/22e3t1353406993.png",intern=TRUE)) character(0) > try(system("convert tmp/318sf1353406993.ps tmp/318sf1353406993.png",intern=TRUE)) character(0) > try(system("convert tmp/4tc1h1353406993.ps tmp/4tc1h1353406993.png",intern=TRUE)) character(0) > try(system("convert tmp/5z0tx1353406993.ps tmp/5z0tx1353406993.png",intern=TRUE)) character(0) > try(system("convert tmp/6mfbb1353406993.ps tmp/6mfbb1353406993.png",intern=TRUE)) character(0) > try(system("convert tmp/7fkgj1353406993.ps tmp/7fkgj1353406993.png",intern=TRUE)) character(0) > try(system("convert tmp/8w3u71353406993.ps tmp/8w3u71353406993.png",intern=TRUE)) character(0) > try(system("convert tmp/9jqqm1353406993.ps tmp/9jqqm1353406993.png",intern=TRUE)) character(0) > try(system("convert tmp/10tkfg1353406993.ps tmp/10tkfg1353406993.png",intern=TRUE)) character(0) > try(system("convert tmp/118sxx1353406993.ps tmp/118sxx1353406993.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 7.116 1.228 8.367