R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(127800,127700,128500,129400,128800,128800,131300,131100,131500,132900,133500,133400,134828,136488,135943,138717,139223,139869,140507,140259,139220,144033,144683,147354,148813,152657,155912,155271,161382,162106,164825,162810,163398,164844,165910,165774,164881,164861,165501,164334,162229,162748,163915,160890,159779,161106,160659,160007,158917,159052,159507,159107,159925,161327,159957,156997,159316,159793,161383,161828,162887,164071,163810,166708,168481,169913,169602,170559,170943)
> par2 = '12'
> par1 = '500'
> 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)
+ c(s.mean, s.median)
+ }
> (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* 152819.1     9.582928    4509.841
t2* 159779.0 -3437.162000    7616.305
> z <- data.frame(cbind(r$t[,1],r$t[,2]))
> colnames(z) <- list('mean','median')
> postscript(file="/var/wessaorg/rcomp/tmp/1olsj1321376068.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> b <- boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
> grid()
> dev.off()
null device 
          1 
> b
$stats
         [,1]   [,2]
[1,] 142357.2 148813
[2,] 150173.5 155912
[3,] 152834.0 159779
[4,] 156158.0 161106
[5,] 162497.0 164071

$n
[1] 500 500

$conf
         [,1]   [,2]
[1,] 152411.1 159412
[2,] 153256.8 160146

$out
 [1] 141111.6 140892.7 140301.4 133657.3 140507.0 136488.0 144683.0 144033.0
 [9] 139223.0 133500.0 140259.0 144683.0 140259.0 139869.0 144033.0 139869.0
[17] 132900.0 147354.0 139223.0 144683.0 147354.0 139223.0 139223.0 139869.0
[25] 144033.0 140507.0 139220.0 144683.0 140507.0 138717.0 147354.0 147354.0
[33] 140507.0 144683.0 140507.0 140259.0 144033.0 147354.0 132900.0 133400.0
[41] 139869.0 139223.0 147354.0 139869.0 144033.0 144033.0 134828.0 140507.0
[49] 147354.0 147354.0 139869.0 144033.0 139869.0 140507.0 138717.0 138717.0
[57] 135943.0 147354.0 144683.0 139869.0 140507.0 136488.0 147354.0 134828.0
[65] 139869.0 144683.0 144033.0 139220.0 140507.0 139223.0 144683.0 134828.0
[73] 131500.0 144033.0 144033.0 144683.0 136488.0 139223.0 139223.0 144683.0
[81] 144683.0 140507.0 139869.0 144683.0 136488.0 147354.0 133500.0 139220.0
[89] 147354.0 134828.0

$group
 [1] 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
[39] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
[77] 2 2 2 2 2 2 2 2 2 2 2 2 2 2

$names
[1] "mean"   "median"

> 
> #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.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/21q7i1321376068.tab") 
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'95% Confidence Intervals',3,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'',1,TRUE)
> a<-table.element(a,'Mean',1,TRUE)
> a<-table.element(a,'Median',1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Lower Bound',1,TRUE)
> a<-table.element(a,b$conf[1,1])
> a<-table.element(a,b$conf[1,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Upper Bound',1,TRUE)
> a<-table.element(a,b$conf[2,1])
> a<-table.element(a,b$conf[2,2])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/3qpy91321376068.tab") 
> 
> try(system("convert tmp/1olsj1321376068.ps tmp/1olsj1321376068.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.855   0.098   0.945