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Type 'q()' to quit R. > x <- c(2851,2672,2755,2721,2946,3036,2282,2212,2922,4301,5764,7132,2541,2475,3031,3266,3776,3230,3028,1759,3595,4474,6838,8357,3113,3006,4047,3523,3937,3986,3260,1573,3528,5211,7614,9254,5375,3088,3718,4514,4520,4539,3663,1643,4739,5428,8314,10651,3633,4292,4154,4121,4647,4753,3965,1723,5048,6922,9858,11331,4016,3975,4510,4276,4968,4677,3523,1821,5222,6873,10803,13916,2639,2899,3370,3740,2927,3986,4217,1738,5221,6424,9842,13076,3934,3162,4286,4676,5010,4874,4633,1659,5951,6981,9851,12670) > par1 = '200' > #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > par1 <- as.numeric(par1) > if (par1 < 10) par1 = 10 > if (par1 > 5000) par1 = 5000 > library(lattice) > library(boot) Attaching package: 'boot' The following object(s) are masked from package:lattice : melanoma > boot.stat <- function(s,i) + { + s.mean <- mean(s[i]) + s.median <- median(s[i]) + s.midrange <- (max(s[i]) + min(s[i])) / 2 + c(s.mean, s.median, s.midrange) + } > (r <- boot(x,boot.stat, R=par1, stype='i')) ORDINARY NONPARAMETRIC BOOTSTRAP Call: boot(data = x, statistic = boot.stat, R = par1, stype = "i") Bootstrap Statistics : original bias std. error t1* 4802.094 20.89594 269.1080 t2* 4084.000 35.60500 190.4788 t3* 7744.500 -177.24000 332.8671 > postscript(file="/var/www/html/freestat/rcomp/tmp/124fu1274798886.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/224fu1274798886.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/3vwex1274798886.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/4vwex1274798886.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/5vwex1274798886.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/6vwex1274798886.ps",horizontal=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/www/html/freestat/rcomp/tmp/755d01274798886.ps",horizontal=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(4148.30208333333, 4624.70833333333, 4822.74479166667, : some notches went outside hinges ('box'): maybe set notch=FALSE > grid() > dev.off() null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/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/www/html/freestat/rcomp/tmp/8u6sb1274798886.tab") > > try(system("convert tmp/124fu1274798886.ps tmp/124fu1274798886.png",intern=TRUE)) character(0) > try(system("convert tmp/224fu1274798886.ps tmp/224fu1274798886.png",intern=TRUE)) character(0) > try(system("convert tmp/3vwex1274798886.ps tmp/3vwex1274798886.png",intern=TRUE)) character(0) > try(system("convert tmp/4vwex1274798886.ps tmp/4vwex1274798886.png",intern=TRUE)) character(0) > try(system("convert tmp/5vwex1274798886.ps tmp/5vwex1274798886.png",intern=TRUE)) character(0) > try(system("convert tmp/6vwex1274798886.ps tmp/6vwex1274798886.png",intern=TRUE)) character(0) > try(system("convert tmp/755d01274798886.ps tmp/755d01274798886.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.657 1.709 2.941