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Type 'q()' to quit R. > x <- c(3592.21,5955.74,4652.25,4211.65,4787.85,3599.73,4174.27,5106.33,5325.75,6604.61,5711.90,6919.30,7048.76,8655.98,6658.53,7247.03,8779.57,6602.49,9832.48,9369.49,8582.76,8206.94,6515.83,8618.10,8505.39,9881.64,9375.29,15642.50,12232.73,6288.93,12473.94,11142.82,10236.32,10581.51,8763.71,10819.04,11636.25,14650.13,10671.38,17468.63,13873.19,13077.58,16866.81,14186.64,19919.87,17681.78,9984.28,17423.09,13514.45,12334.57,12274.56,11752.23,13054.00,12460.98,8626.68,13722.62,12066.22,6798.83,6593.82,6606.19,6315.28,7232.95,6747.44,7803.61,6700.31,5369.53,8081.19,10718.39,9447.21,6815.10,5497.80,6805.31) > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > par1 <- as.numeric(par1) > if (par1 < 10) par1 = 10 > if (par1 > 5000) par1 = 5000 > library(lattice) > library(boot) Attaching package: 'boot' The following object(s) are masked from package:lattice : melanoma > boot.stat <- function(s,i) + { + s.mean <- mean(s[i]) + s.median <- median(s[i]) + s.midrange <- (max(s[i]) + min(s[i])) / 2 + c(s.mean, s.median, s.midrange) + } > (r <- boot(x,boot.stat, R=par1, stype='i')) ORDINARY NONPARAMETRIC BOOTSTRAP Call: boot(data = x, statistic = boot.stat, R = par1, stype = "i") Bootstrap Statistics : original bias std. error t1* 9409.476 -12.79941 444.2496 t2* 8641.330 65.30363 629.0297 t3* 11756.040 -407.84468 595.2677 > postscript(file="/var/www/html/rcomp/tmp/1cqb11273511362.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2cqb11273511362.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3cqb11273511362.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4mzs41273511362.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5mzs41273511362.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/6mzs41273511362.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/rcomp/tmp/7xqsp1273511362.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(8356.14083333333, 9116.71840277778, 9360.72222222222, : some notches went outside hinges ('box'): maybe set notch=FALSE > grid() > dev.off() null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/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/rcomp/tmp/8ti7x1273511362.tab") > > try(system("convert tmp/1cqb11273511362.ps tmp/1cqb11273511362.png",intern=TRUE)) character(0) > try(system("convert tmp/2cqb11273511362.ps tmp/2cqb11273511362.png",intern=TRUE)) character(0) > try(system("convert tmp/3cqb11273511362.ps tmp/3cqb11273511362.png",intern=TRUE)) character(0) > try(system("convert tmp/4mzs41273511362.ps tmp/4mzs41273511362.png",intern=TRUE)) character(0) > try(system("convert tmp/5mzs41273511362.ps tmp/5mzs41273511362.png",intern=TRUE)) character(0) > try(system("convert tmp/6mzs41273511362.ps tmp/6mzs41273511362.png",intern=TRUE)) character(0) > try(system("convert tmp/7xqsp1273511362.ps tmp/7xqsp1273511362.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.711 1.040 2.089