R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(1.579,2.146,2.462,3.695,4.831,5.134,6.250,5.760,6.249,2.917,1.741,2.359,1.511,2.059,2.635,2.867,4.403,5.720,4.502,5.749,5.627,2.846,1.762,2.429,1.169,2.154,2.249,2.687,4.359,5.382,4.459,6.398,4.596,3.024,1.887,2.070,1.351,2.218,2.461,3.028,4.784,4.975,4.607,6.249,4.809,3.157,1.910,2.228,1.594,2.467,2.222,3.607,4.685,4.962,5.770,5.480,5.000,3.228,1.993,2.288,1.580,2.111,2.192,3.601,4.665,4.876,5.813,5.589,5.331,3.075,2.002,2.306,1.507,1.992,2.487,3.490,4.647,5.594,5.611,5.788,6.204,3.013,1.931,2.549,1.504,2.090,2.702,2.939,4.500,6.208,6.415,5.657,5.964,3.163,1.997,2.422)
> 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* 3.606823 -0.005733917  0.04824879
t2* 3.051500  0.017624000  0.08169283
> 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/16hmy1290938336.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,] 3.473969 2.8920
[2,] 3.569250 3.0240
[3,] 3.601089 3.0515
[4,] 3.634911 3.1190
[5,] 3.730167 3.2280

$n
[1] 500 500

$conf
         [,1]     [,2]
[1,] 3.596449 3.044787
[2,] 3.605728 3.058213

$out
 [1] 3.468667 3.466135 3.359000 2.867000 2.867000 2.856500 3.359000 2.856500
 [9] 2.856500 2.856500 3.359000 2.856500 2.867000

$group
 [1] 1 1 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/2di1a1290938336.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/36a1d1290938336.tab") 
> try(system("convert tmp/16hmy1290938336.ps tmp/16hmy1290938336.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
   0.76    0.18    1.53