R version 2.11.1 (2010-05-31)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(38,32,35,33,37,29,31,36,35,38,31,34,35,38,37,33,32,38,38,32,33,31,38,39,32,32,35,37,33,33,28,32,31,37,30,33,31,33,31,33,32,33,32,33,28,35,39,34,38,32,38,30,33,38,32,32,34,34,36,34,28,34,35,35,31,37,35,27,40,37,36,38,39,41,27,30,37,31,31,27,36,38,37,33,34,31,39,34,32,33,36,32,41,28,30,36,35,31,34,36,36,35,37,28,39,32,35,39,35,42,34,33,41,33,34,32,40,40,35,36,37,27,39,38,31,33,32,39,36,33,33,32,37,30,38,29,22,35,35,34,35,34,34,35,23,31,27,36,31,32,39,37,38,39,34,31,32,37,36,32,35,36)
> 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* 34.09259 -0.02508642   0.2791518
t2* 34.00000  0.03100000   0.5070040
> z <- data.frame(cbind(r$t[,1],r$t[,2]))
Warning message:
In data.row.names(row.names, rowsi, i) :
  some row.names duplicated: 2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271 [... truncated]
> colnames(z) <- list('mean','median')
> postscript(file="/var/www/rcomp/tmp/1a7a81290856378.ps",horizontal=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,] 33.40123   34
[2,] 33.87963   34
[3,] 34.06173   34
[4,] 34.24074   34
[5,] 34.75926   34

$n
[1] 500 500

$conf
         [,1] [,2]
[1,] 34.03621   34
[2,] 34.08724   34

$out
  [1] 33.33333 34.79012 34.82099 34.81481 34.85185 34.78395 33.32099 33.20370
  [9] 35.00000 35.00000 33.00000 35.00000 33.00000 35.00000 34.50000 33.00000
 [17] 35.00000 33.00000 33.00000 33.00000 33.50000 34.50000 35.00000 33.00000
 [25] 35.00000 33.00000 33.00000 33.00000 35.00000 33.50000 33.00000 33.00000
 [33] 35.00000 33.00000 35.00000 34.50000 33.00000 35.00000 33.00000 35.00000
 [41] 35.00000 34.50000 34.50000 35.00000 33.00000 35.00000 35.00000 34.50000
 [49] 35.00000 33.50000 35.00000 35.00000 34.50000 33.00000 35.00000 33.00000
 [57] 33.00000 35.00000 35.00000 33.00000 33.00000 33.00000 35.00000 33.00000
 [65] 34.50000 35.00000 33.00000 33.50000 33.00000 35.00000 33.50000 33.00000
 [73] 33.50000 33.00000 33.00000 34.50000 33.00000 35.00000 35.00000 33.00000
 [81] 35.00000 35.00000 35.00000 33.00000 35.00000 33.00000 35.00000 33.50000
 [89] 35.00000 35.00000 33.00000 35.00000 35.00000 35.00000 34.50000 35.00000
 [97] 35.00000 35.00000 35.00000 35.00000 33.00000 35.00000 33.00000 33.00000
[105] 34.50000 35.00000 33.00000 35.00000 33.00000 35.00000 33.50000 33.00000
[113] 35.00000 35.00000 33.00000 34.50000 33.00000 34.50000 33.00000 35.00000
[121] 34.50000 35.00000 35.00000 35.00000 35.00000 33.50000 35.00000 35.00000
[129] 33.00000 35.00000 33.00000 35.00000 35.00000 33.50000 33.00000 33.00000
[137] 35.00000 33.00000 35.00000 33.50000 33.50000 33.00000 35.00000 35.00000
[145] 35.00000 34.50000 35.00000 33.00000 33.00000 35.00000 33.00000 35.00000
[153] 33.00000 35.00000 33.00000 33.00000 35.00000

$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
 [38] 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
 [75] 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
[112] 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
[149] 2 2 2 2 2 2 2 2 2

$names
[1] "mean"   "median"

> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/www/rcomp/tmp/2h8tc1290856379.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/www/rcomp/tmp/32r901290856379.tab") 
> 
> try(system("convert tmp/1a7a81290856378.ps tmp/1a7a81290856378.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.080   0.250   1.292