R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(103,102.4,102,101.8,101.6,101.4,101.3,101.4,101.7,102.4,103.1,103.8,104.4,105,105.7,106.4,107.1,107.9,108.8,109.6,110.3,110.8,111.2,111.7,112.3,112.8,113.1,113.1,113.1,113.2,113.1,112.8,112.5,112.3,112.5,112.9,113.5,114.1,114.6,114.9,115.4,115.7,116.1,116.5,117.1,117.5,117.7,117.7,117.7,117.6,117.5,117.6,117.9,118.2,118.5,118.7,118.8,118.9,119,119)
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = ''
> par2 = '12'
> par1 = '500'
> ylab = ''
> xlab = ''
> main = ''
> 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* 111.4783 -0.09222    2.211186
t2* 112.8500 -0.67510    3.435780
> 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/html/rcomp/tmp/10b1x1229978002.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,] 105.7250 107.1
[2,] 109.9158 111.0
[3,] 111.5175 112.8
[4,] 112.9083 113.8
[5,] 116.2550 117.9

$n
[1] 500 500

$conf
         [,1]     [,2]
[1,] 111.3061 112.6022
[2,] 111.7289 112.9978

$out
 [1] 104.6233 104.8900 104.8767 103.1000 103.1000 103.8000 106.0500 105.0000
 [9] 106.0500 103.0500 106.7500 106.7500 106.7500 105.0000 104.4000 102.7000
[17] 102.4000 103.4500 103.0500 106.7500 105.3500 104.7000 103.1000 103.0500
[25] 106.4000 106.4000 104.1000 102.7000 103.1000 106.7500 105.0000 105.7000
[33] 105.0000 105.7000 105.7000 106.4000 106.7500 105.7000 105.3500 105.3500
[41] 105.7000 104.4000 103.8000 105.3500 106.7500 103.8000 105.3500 106.0500
[49] 106.7500 105.7000 106.0500 105.7000 103.0000 105.3500 104.7000 102.4000
[57] 105.3500 103.0000 106.4000

$group
 [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 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/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/html/rcomp/tmp/24nmw1229978002.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/html/rcomp/tmp/3l2y31229978002.tab") 
> 
> system("convert tmp/10b1x1229978002.ps tmp/10b1x1229978002.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.751   0.195   4.474