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Type 'q()' to quit R. > x <- c(25,24,21,23,17,19,18,27,23,23,29,21,26,25,25,23,26,20,29,24,23,24,30,22,22,13,24,17,24,21,23,24,24,24,23,26,24,21,23,28,23,22,24,21,23,23,20,23,21,27,12,15,22,21,21,20,24,24,29,25,14,30,19,29,25,25,25,16,25,28,24,25,21,22,20,25,27,21,13,26,26,25,22,19,23,25,15,21,23,25,24,24,21,24,22,24,28,21,17,28,24,10,20,22,19,22,22,26,24,22,20,20,15,20,20,24,22,29,23,24,22,16,23,27,16,21,26,22,23,19,18,24,24,29,22,24,22,12,26,18,22,24,21,15,23,22,22,24,23,13) > 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* 22.37333 0.02193333 0.2935305 t2* 23.00000 -0.08100000 0.3914658 > 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/1msf11292689375.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,] 21.66000 23 [2,] 22.19333 23 [3,] 22.37333 23 [4,] 22.59667 23 [5,] 23.14000 23 $n [1] 500 500 $conf [,1] [,2] [1,] 22.34483 23 [2,] 22.40183 23 $out [1] 23.21333 23.22000 23.23333 24.00000 22.00000 24.00000 23.50000 22.00000 [9] 22.50000 22.50000 22.00000 22.00000 22.00000 24.00000 22.00000 22.00000 [17] 24.00000 22.50000 22.00000 22.50000 22.50000 22.00000 22.00000 23.50000 [25] 22.00000 22.00000 24.00000 22.50000 22.00000 22.00000 22.00000 24.00000 [33] 22.00000 24.00000 22.50000 22.00000 22.00000 22.00000 22.50000 23.50000 [41] 22.50000 22.00000 22.00000 23.50000 22.00000 22.50000 24.00000 22.00000 [49] 23.50000 22.00000 22.50000 22.00000 23.50000 22.00000 23.50000 24.00000 [57] 22.00000 22.50000 22.00000 24.00000 22.00000 22.00000 22.00000 22.00000 [65] 22.00000 22.00000 22.00000 24.00000 24.00000 22.00000 22.00000 22.50000 [73] 22.00000 22.00000 24.00000 22.50000 22.00000 23.50000 22.00000 24.00000 [81] 22.00000 22.00000 24.00000 24.00000 22.00000 22.00000 22.00000 22.50000 [89] 23.50000 22.00000 24.00000 22.00000 22.00000 23.50000 22.00000 22.50000 [97] 24.00000 22.00000 22.00000 22.00000 22.00000 22.50000 22.00000 $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 [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 $names [1] "mean" "median" > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Estimation Results of Blocked Bootstrap',6,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'statistic',header=TRUE) > a<-table.element(a,'Q1',header=TRUE) > a<-table.element(a,'Estimate',header=TRUE) > a<-table.element(a,'Q3',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'IQR',header=TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'mean',header=TRUE) > q1 <- quantile(r$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$t[,2]))) > a<-table.element(a,q3-q1) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/2btud1292689375.tab") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'95% Confidence Intervals',3,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'',1,TRUE) > a<-table.element(a,'Mean',1,TRUE) > a<-table.element(a,'Median',1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Lower Bound',1,TRUE) > a<-table.element(a,b$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/3l2by1292689375.tab") > > try(system("convert tmp/1msf11292689375.ps tmp/1msf11292689375.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.808 0.190 1.732