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Type 'q()' to quit R. > x <- c(7.72,7.67,7.84,7.79,7.83,7.94,8.02,8.06,8.12,8.13,7.97,8.01,8,7.9,7.99,8.02,8.08,8.02,8.07,8.11,8.19,8.16,8.08,8.22,8.15,8.19,8.31,8.3,8.34,8.31,8.38,8.34,8.44,8.64,8.6,8.61,8.54,8.69,8.73,8.91,9.01,9.08,8.94,9.03,9.02,8.96,9.03,8.94,8.95,8.95,8.99,8.93,8.98,8.95,9.02,8.92,9.1,9.06,8.97,8.89,8.99,8.79,8.83,8.61,8.71,8.91,8.91,8.89,8.98,9,8.99,8.88) > par3 = '0' > par2 = '5' > par1 = '750' > par3 <- '0' > par2 <- '5' > par1 <- '750' > #'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)$M + c(s.mean, s.median, s.midrange, s.mode, s.kernelmode) + } > (r <- boot(x,boot.stat, R=par1, stype='i')) ORDINARY NONPARAMETRIC BOOTSTRAP Call: boot(data = x, statistic = boot.stat, R = par1, stype = "i") Bootstrap Statistics : original bias std. error t1* 8.522639 0.002769630 0.05152403 t2* 8.610000 -0.008833333 0.15092772 t3* 8.385000 0.008860000 0.02522000 t4* 8.717500 -0.049577407 0.34816225 t5* 8.963890 -0.134804109 0.32037451 Warning messages: 1: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 2: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 3: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 4: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 5: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 6: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal 7: In .deal.ties(ny, i, tie.action, tie.limit) : encountered a tie, and the difference between minimal and maximal value is > length('x') * 'tie.limit' the distribution could be multimodal > postscript(file="/var/wessaorg/rcomp/tmp/1fn161353362718.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/20jgj1353362718.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3i1z91353362718.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4spj31353362718.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5fsvm1353362718.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$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/65zpf1353362718.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/7bnzc1353362718.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/81boi1353362718.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9cocq1353362718.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,4],col='black',main='Density Plot',xlab='mode') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/106t6y1353362718.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/11pz281353362718.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(8.39652777777778, 8.49236111111111, 8.52645833333333, : 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/123khw1353362718.tab") > > try(system("convert tmp/1fn161353362718.ps tmp/1fn161353362718.png",intern=TRUE)) character(0) > try(system("convert tmp/20jgj1353362718.ps tmp/20jgj1353362718.png",intern=TRUE)) character(0) > try(system("convert tmp/3i1z91353362718.ps tmp/3i1z91353362718.png",intern=TRUE)) character(0) > try(system("convert tmp/4spj31353362718.ps tmp/4spj31353362718.png",intern=TRUE)) character(0) > try(system("convert tmp/5fsvm1353362718.ps tmp/5fsvm1353362718.png",intern=TRUE)) character(0) > try(system("convert tmp/65zpf1353362718.ps tmp/65zpf1353362718.png",intern=TRUE)) character(0) > try(system("convert tmp/7bnzc1353362718.ps tmp/7bnzc1353362718.png",intern=TRUE)) character(0) > try(system("convert tmp/81boi1353362718.ps tmp/81boi1353362718.png",intern=TRUE)) character(0) > try(system("convert tmp/9cocq1353362718.ps tmp/9cocq1353362718.png",intern=TRUE)) character(0) > try(system("convert tmp/106t6y1353362718.ps tmp/106t6y1353362718.png",intern=TRUE)) character(0) > try(system("convert tmp/11pz281353362718.ps tmp/11pz281353362718.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 18.754 1.303 20.225