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Type 'q()' to quit R. > x <- c(100.34,100.21,100.44,101.59,102.44,103.1,103.34,103.44,103.35,103.67,104.13,104.27,104.75,104.82,104.69,104.87,104.74,104.85,104.8,104.13,104.02,104.46,105.58,106.94,108.41,109.05,108.75,108.96,108.46,107.51,107.27,106.72,108.94,112.02,112.46,113.56,113.64,114.13,116.44,117.71,117.57,117.25,117.33,117.36,117.18,117.21,117.44,117.54,119.07,118.5,118.69,118.38,118.45,117.88,118.52,118.26,118.39,117.87,118.36,117.91) > par2 = '12' > par1 = '750' > par2 <- '12' > par1 <- '750' > #'GNU S' R Code compiled by R2WASP v. 1.2.291 () > #Author: root > #To cite this work: Wessa P., (2012), Blocked Bootstrap Plot for Central Tendency (v1.0.4) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_bootstrapplot.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > # > par1 <- as.numeric(par1) > par2 <- as.numeric(par2) > if (par1 < 10) par1 = 10 > if (par1 > 5000) par1 = 5000 > if (par2 < 3) par2 = 3 > if (par2 > length(x)) par2 = length(x) > library(lattice) > library(boot) Attaching package: 'boot' The following object(s) are masked from 'package:lattice': melanoma > boot.stat <- function(s) + { + s.mean <- mean(s) + s.median <- median(s) + s.midrange <- (max(s) + min(s)) / 2 + c(s.mean, s.median, s.midrange) + } > (r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed')) BLOCK BOOTSTRAP FOR TIME SERIES Fixed Block Length of 12 Call: tsboot(tseries = x, statistic = boot.stat, R = par1, l = 12, sim = "fixed") Bootstrap Statistics : original bias std. error t1* 110.3693 0.1875758 2.399406 t2* 108.8450 1.7980733 4.896246 t3* 109.6400 0.3455133 0.965656 > postscript(file="/var/wessaorg/rcomp/tmp/1u7kr1335029253.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/27thm1335029253.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/307hs1335029253.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4z5a61335029253.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5g1nq1335029253.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/6iqog1335029253.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/7acmo1335029253.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(104.025333333333, 108.752333333333, 110.475833333333, : 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 Blocked 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/895w41335029253.tab") > > try(system("convert tmp/1u7kr1335029253.ps tmp/1u7kr1335029253.png",intern=TRUE)) character(0) > try(system("convert tmp/27thm1335029253.ps tmp/27thm1335029253.png",intern=TRUE)) character(0) > try(system("convert tmp/307hs1335029253.ps tmp/307hs1335029253.png",intern=TRUE)) character(0) > try(system("convert tmp/4z5a61335029253.ps tmp/4z5a61335029253.png",intern=TRUE)) character(0) > try(system("convert tmp/5g1nq1335029253.ps tmp/5g1nq1335029253.png",intern=TRUE)) character(0) > try(system("convert tmp/6iqog1335029253.ps tmp/6iqog1335029253.png",intern=TRUE)) character(0) > try(system("convert tmp/7acmo1335029253.ps tmp/7acmo1335029253.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.967 0.418 3.390