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Type 'q()' to quit R. > x <- c(100.32,100.33,100.35,100.38,100.44,100.47,100.47,100.48,100.48,100.49,100.52,100.53,100.62,100.89,100.92,100.93,100.97,100.98,101.01,101.02,101.07,101.1,101.11,101.19,101.31,101.52,101.56,101.61,101.65,101.66,101.75,101.83,101.98,102.06,102.07,102.1,102.42,102.91,102.91,103.11,103.14,103.14,103.23,103.23,103.26,103.3,103.32,103.44,103.54,103.86,103.88,103.88,103.89,103.98,103.98,103.98,104.24,104.29,104.29,104.31,104.41,104.54,104.67,104.8) > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > par1 <- as.numeric(par1) > if (par1 < 10) par1 = 10 > if (par1 > 5000) par1 = 5000 > library(lattice) > library(boot) Attaching package: 'boot' The following object(s) are masked from 'package:lattice': melanoma > boot.stat <- function(s,i) + { + s.mean <- mean(s[i]) + s.median <- median(s[i]) + s.midrange <- (max(s[i]) + min(s[i])) / 2 + c(s.mean, s.median, s.midrange) + } > (r <- boot(x,boot.stat, R=par1, stype='i')) ORDINARY NONPARAMETRIC BOOTSTRAP Call: boot(data = x, statistic = boot.stat, R = par1, stype = "i") Bootstrap Statistics : original bias std. error t1* 102.2206 0.02456875 0.21955399 t2* 101.9050 0.13600000 0.46146616 t3* 102.5600 -0.03160000 0.04600843 > postscript(file="/var/wessaorg/rcomp/tmp/1n6k21321959496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/295v11321959496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3ks9e1321959496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4rvnz1321959496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/57pg21321959496.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/6wtx71321959496.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/wessaorg/rcomp/tmp/72kxw1321959496.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(101.79203125, 102.105, 102.246640625, 102.40078125, : 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,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/wessaorg/rcomp/tmp/8ivx61321959496.tab") > > try(system("convert tmp/1n6k21321959496.ps tmp/1n6k21321959496.png",intern=TRUE)) character(0) > try(system("convert tmp/295v11321959496.ps tmp/295v11321959496.png",intern=TRUE)) character(0) > try(system("convert tmp/3ks9e1321959496.ps tmp/3ks9e1321959496.png",intern=TRUE)) character(0) > try(system("convert tmp/4rvnz1321959496.ps tmp/4rvnz1321959496.png",intern=TRUE)) character(0) > try(system("convert tmp/57pg21321959496.ps tmp/57pg21321959496.png",intern=TRUE)) character(0) > try(system("convert tmp/6wtx71321959496.ps tmp/6wtx71321959496.png",intern=TRUE)) character(0) > try(system("convert tmp/72kxw1321959496.ps tmp/72kxw1321959496.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.153 0.355 2.515