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Type 'q()' to quit R. > x <- c(17.1,13.4,15.3,14,9.7,13.7,13.7,12.5,9.8,7,-1.9,-2.9,-6.8,-10.4,-17.2,-19.8,-16.8,-23.2,-21.7,-17.6,-13,-12.6,-4,-0.2,3.1,6.5,19.2,26.6,26.6,31.4,31.2,26.4,20.7,20.7,15,13.3,8.7,10.2,4.3,-0.1,-4.6,-3.9,-3.5,-3.4,-2.5,-1.1,0.3,-0.9,3.6,2.7,-0.2,-1,5.8,6.4,9.6,13.2,10.6,10.9,12.9,15.9,12.2,9.1,9,17.4,14.7,17,13.7,9.5,14.8,13.6,12.6,8.9,10.2,12.7,16,10.4,9.9,9.5,8.6,10,3.5,-4.2,-4.4,-1.5,-0.1,0.8,-2.4,-1.2,0.2,-1.9,-1.6,-4.2,-2.2,6.2,5.7,3.1,1.1,-0.9,0.1,-4,-4,-5.3,-8,-6.3,-3.6,-3.5,-5.1,-3.3) > par1 = '50' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > par1 <- as.numeric(par1) > if (par1 < 10) par1 = 10 > if (par1 > 5000) par1 = 5000 > library(lattice) > library(boot) Attaching package: 'boot' The following object(s) are masked from package:lattice : melanoma > boot.stat <- function(s,i) + { + s.mean <- mean(s[i]) + s.median <- median(s[i]) + s.midrange <- (max(s[i]) + min(s[i])) / 2 + c(s.mean, s.median, s.midrange) + } > (r <- boot(x,boot.stat, R=par1, stype='i')) ORDINARY NONPARAMETRIC BOOTSTRAP Call: boot(data = x, statistic = boot.stat, R = par1, stype = "i") Bootstrap Statistics : original bias std. error t1* 4.49537 0.1548333 0.9821643 t2* 3.95000 0.6790000 2.3275872 t3* 4.10000 0.1440000 1.4590897 > postscript(file="/var/yougetitorg/rcomp/tmp/1vgcs1304447171.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean') > grid() > dev.off() null device 1 > postscript(file="/var/yougetitorg/rcomp/tmp/2pyiq1304447171.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median') > grid() > dev.off() null device 1 > postscript(file="/var/yougetitorg/rcomp/tmp/3loqt1304447171.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange') > grid() > dev.off() null device 1 > postscript(file="/var/yougetitorg/rcomp/tmp/4hypf1304447171.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean') > dev.off() null device 1 > postscript(file="/var/yougetitorg/rcomp/tmp/5x1do1304447171.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median') > dev.off() null device 1 > postscript(file="/var/yougetitorg/rcomp/tmp/605ly1304447171.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange') > dev.off() null device 1 > z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3])) > colnames(z) <- list('mean','median','midrange') > postscript(file="/var/yougetitorg/rcomp/tmp/7fk431304447171.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(3.10185185185185, 3.82314814814815, 4.46990740740741, : some notches went outside hinges ('box'): maybe set notch=FALSE > grid() > dev.off() null device 1 > > #Note: the /var/yougetitorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/yougetitorg/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,q1) > a<-table.element(a,r$t0[1]) > a<-table.element(a,q3) > a<-table.element(a,sqrt(var(r$t[,1]))) > a<-table.element(a,q3-q1) > 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,q1) > a<-table.element(a,r$t0[2]) > a<-table.element(a,q3) > a<-table.element(a,sqrt(var(r$t[,2]))) > a<-table.element(a,q3-q1) > 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,q1) > a<-table.element(a,r$t0[3]) > a<-table.element(a,q3) > a<-table.element(a,sqrt(var(r$t[,3]))) > a<-table.element(a,q3-q1) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/yougetitorg/rcomp/tmp/8ym121304447171.tab") > > try(system("convert tmp/1vgcs1304447171.ps tmp/1vgcs1304447171.png",intern=TRUE)) character(0) > try(system("convert tmp/2pyiq1304447171.ps tmp/2pyiq1304447171.png",intern=TRUE)) character(0) > try(system("convert tmp/3loqt1304447171.ps tmp/3loqt1304447171.png",intern=TRUE)) character(0) > try(system("convert tmp/4hypf1304447171.ps tmp/4hypf1304447171.png",intern=TRUE)) character(0) > try(system("convert tmp/5x1do1304447171.ps tmp/5x1do1304447171.png",intern=TRUE)) character(0) > try(system("convert tmp/605ly1304447171.ps tmp/605ly1304447171.png",intern=TRUE)) character(0) > try(system("convert tmp/7fk431304447171.ps tmp/7fk431304447171.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.010 1.230 2.588