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Type 'q()' to quit R. > x <- c(61.712,62.084,61.406,60.724,58.904,58.722,59.704,60.674,59.813,60.568,61.401,61.427,61.080,61.999,63.888,66.284,67.309,66.685,65.404,65.045,63.867,64.156,62.224,63.193,64.256,66.153,68.072,68.245,68.741,67.795,67.315,67.245,66.448,69.112,71.787,74.366,76.337,77.618,77.090,76.925,78.384,80.462,82.765,85.033,83.608,81.813,81.467,80.708,80.631,79.133,77.396,75.491,74.267,72.882,71.286,70.737,67.425,67.530,67.157,67.215,66.268,66.053,54.905,54.459,51.159,44.725,40.184,44.094,46.904,47.141,45.052,42.758,41.388,41.154,40.019,39.928,38.598,36.584,32.566,30.140,27.713,25.380,23.823,21.376,18.696,16.304,14.203,11.807,7.551,4.215,3.346,3.010,2.849,2.485,1.744,1.221,803,553,314,204,125,55,53,27,10,6) > 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* 69.72613 -0.2266443 12.980110 t2* 62.15400 -1.1788820 7.426451 > 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/19fsd1290703734.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,] 39.08320 52.0795 [2,] 59.79899 60.1905 [3,] 68.27009 62.1540 [4,] 77.39349 66.1280 [5,] 103.74454 74.3660 $n [1] 500 500 $conf [,1] [,2] [1,] 67.02687 61.73446 [2,] 69.51331 62.57354 $out [1] 104.6563 107.5477 105.6245 105.4407 45.8145 49.1500 44.7250 42.4545 [9] 45.9780 40.1015 38.5980 47.0225 46.9040 49.1500 44.8885 51.1590 [17] 47.1410 45.9780 44.4095 44.7250 75.4910 41.3880 41.1540 45.0520 [25] 45.9780 47.1410 47.0225 50.0705 49.1500 45.9780 49.1500 41.2710 [33] 49.1500 44.0940 45.9780 46.9040 43.9050 51.1590 43.4260 41.1540 [41] 47.0225 42.0730 30.1400 42.0730 47.0225 47.0225 75.9140 47.1410 [49] 42.0730 47.1410 51.1590 45.0520 45.9780 45.9780 39.2630 76.9250 [57] 51.1590 39.9280 41.2710 44.0940 16.3040 51.1590 42.7580 50.0705 [65] 38.5980 44.7250 42.0730 39.2630 45.0520 44.4095 45.0520 $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 $names [1] "mean" "median" > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Estimation Results of Blocked Bootstrap',6,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'statistic',header=TRUE) > a<-table.element(a,'Q1',header=TRUE) > a<-table.element(a,'Estimate',header=TRUE) > a<-table.element(a,'Q3',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'IQR',header=TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'mean',header=TRUE) > q1 <- quantile(r$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$t[,2]))) > a<-table.element(a,q3-q1) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/2n7q41290703734.tab") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'95% Confidence Intervals',3,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'',1,TRUE) > a<-table.element(a,'Mean',1,TRUE) > a<-table.element(a,'Median',1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Lower Bound',1,TRUE) > a<-table.element(a,b$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/397691290703734.tab") > > try(system("convert tmp/19fsd1290703734.ps tmp/19fsd1290703734.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.742 0.186 1.609