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(68.897,38.683,44.720,39.525,45.315,50.380,40.600,36.279,42.438,38.064,31.879,11.379,70.249,39.253,47.060,41.697,38.708,49.267,39.018,32.228,40.870,39.383,34.571,12.066,70.938,34.077,45.409,40.809,37.013,44.953,37.848,32.745,39.401,34.931,33.008,8.620,68.906,39.556,50.669,36.432,40.891,48.428,36.222,33.425,39.401,37.967,34.801,12.657,69.116,41.519,51.321,38.529,41.547,52.073,38.401,40.898,40.439,41.888,37.898,8.771,68.184,50.530,47.221,41.756,45.633,48.138,39.486,39.341,41.117,41.629,29.722,7.054,56.676,34.870,35.117,30.169,30.936,35.699,33.228,27.733,33.666,35.429,27.438,8.170,63.410,38.040,45.389,37.353,37.024,50.957,37.994,36.454,46.080,43.373,37.395)
> 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* 39.75207  3.425263e-05   1.0652751
t2* 39.34100 -2.622520e-01   0.9736849
> z <- data.frame(cbind(r$t[,1],r$t[,2]))
> colnames(z) <- list('mean','median')
> postscript(file="/var/wessaorg/rcomp/tmp/1z41l1321874477.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,] 37.15789 37.848
[2,] 39.10219 38.683
[3,] 39.81456 39.341
[4,] 40.43675 39.486
[5,] 42.39914 40.600

$n
[1] 500 500

$conf
         [,1]     [,2]
[1,] 39.72026 39.28426
[2,] 39.90886 39.39774

$out
 [1] 37.04148 37.06886 36.88572 37.02663 37.02212 36.58646 36.56135 36.33823
 [9] 40.87000 36.43200 37.01300 37.39500 36.27900 40.80900 40.89800 35.69900
[17] 40.87000 40.80900 37.02400 40.80900 36.22200 37.35300 40.89800 37.35300
[25] 36.22200 37.39500 40.89800 37.39500 37.35300 40.80900 40.89100 37.39500
[33] 40.89100 40.89100 36.22200 37.01300 40.89800 37.39500 35.69900 40.80900
[41] 40.89800 37.35300 40.87000 37.02400 35.69900 37.35300 40.89800 35.69900
[49] 35.42900 36.45400 36.43200 37.02400 36.27900 37.02400 36.22200 37.02400
[57] 40.89800 40.89800 36.45400

$group
 [1] 1 1 1 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
[39] 2 2 2 2 2 2 2 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/23ke91321874478.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/39jwd1321874478.tab") 
> 
> try(system("convert tmp/1z41l1321874477.ps tmp/1z41l1321874477.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.873   0.076   0.944