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Type 'q()' to quit R. > x <- c(10.92,10.98,11.15,11.19,11.33,11.38,11.4,11.45,11.56,11.61,11.82,11.77,11.85,11.82,11.92,11.86,11.87,11.94,11.86,11.92,11.83,11.91,11.93,11.99,11.96,12.12,11.85,12.01,12.1,12.21,12.31,12.31,12.39,12.35,12.41,12.51,12.27,12.51,12.44,12.47,12.51,12.58,12.5,12.52,12.59,12.51,12.67,12.64,12.54,12.6,12.67,12.62,12.72,12.85,12.85,12.82,12.79,12.94,12.71,12.56,12.64,12.7,12.74,12.85,12.84,12.83,12.88,13.07,12.99,13.2,13.23,13.18) > par2 = '12' > par1 = '50' > par2 <- '12' > par1 <- '50' > #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_bootstrapplot.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > # > par1 <- as.numeric(par1) > par2 <- as.numeric(par2) > if (par1 < 10) par1 = 10 > if (par1 > 5000) par1 = 5000 > if (par2 < 3) par2 = 3 > if (par2 > length(x)) par2 = length(x) > library(lattice) > library(boot) Attaching package: 'boot' The following object(s) are masked from 'package:lattice': melanoma > boot.stat <- function(s) + { + s.mean <- mean(s) + s.median <- median(s) + s.midrange <- (max(s) + min(s)) / 2 + c(s.mean, s.median, s.midrange) + } > (r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed')) BLOCK BOOTSTRAP FOR TIME SERIES Fixed Block Length of 12 Call: tsboot(tseries = x, statistic = boot.stat, R = par1, l = 12, sim = "fixed") Bootstrap Statistics : original bias std. error t1* 12.27528 0.003336111 0.1672762 t2* 12.42500 -0.100100000 0.2621642 t3* 12.07500 0.046800000 0.1483231 > postscript(file="/var/fisher/rcomp/tmp/1lo2s1366382300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/28zm71366382300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/3t4ob1366382300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/4muoq1366382300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/5jaer1366382301.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/6quzy1366382301.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/fisher/rcomp/tmp/7ewa41366382301.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(11.8983333333333, 12.18875, 12.2784027777778, : some notches went outside hinges ('box'): maybe set notch=FALSE > grid() > dev.off() null device 1 > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/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/fisher/rcomp/tmp/89qrw1366382301.tab") > > try(system("convert tmp/1lo2s1366382300.ps tmp/1lo2s1366382300.png",intern=TRUE)) character(0) > try(system("convert tmp/28zm71366382300.ps tmp/28zm71366382300.png",intern=TRUE)) character(0) > try(system("convert tmp/3t4ob1366382300.ps tmp/3t4ob1366382300.png",intern=TRUE)) character(0) > try(system("convert tmp/4muoq1366382300.ps tmp/4muoq1366382300.png",intern=TRUE)) character(0) > try(system("convert tmp/5jaer1366382301.ps tmp/5jaer1366382301.png",intern=TRUE)) character(0) > try(system("convert tmp/6quzy1366382301.ps tmp/6quzy1366382301.png",intern=TRUE)) character(0) > try(system("convert tmp/7ewa41366382301.ps tmp/7ewa41366382301.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.323 0.484 3.807