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Type 'q()' to quit R. > x <- c(43,30,30,54,30,16,42,0,30,44,70,30,5,30,62,91,41,73,60,20,4,60,62,60,76,65,60,88,16,65,35,70,21,60,100,65,80,65,60,31,55,74,32,10,20,40,55,70,80,50,55,29,70,50,60,60,27,38,70,15,40,37,10,75,60,55,91,29,50,10,57,45,70,38,70,40,61,15,25,54,36,50,68,14,68,100,74,59,50,60,60,70,45,60,21,0,65,33,70,20,60,65,60,53,71,32,70,60,60,50,25,20,80,53,39,53,39,70,60,77,80,50,69,70,36,30,57,80,91,8,60,63,60,18,39,41,50,65,80,68,58,30,60,100) > 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* 50.82639 0.08059722 1.822506 t2* 55.00000 1.04400000 3.095032 > 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/1pckj1289838652.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,] 46.57639 47.5 [2,] 49.78125 54.0 [3,] 50.90278 55.0 [4,] 52.00347 59.0 [5,] 55.24306 60.0 $n [1] 500 500 $conf [,1] [,2] [1,] 50.74576 54.6467 [2,] 51.05980 55.3533 $out [1] 55.64583 55.73611 55.56250 45.83333 55.54861 55.40972 45.79861 46.09028 [9] 45.00000 44.00000 45.00000 $group [1] 1 1 1 1 1 1 1 1 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$t[,2]))) > a<-table.element(a,q3-q1) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/2wvhc1289838652.tab") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'95% Confidence Intervals',3,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'',1,TRUE) > a<-table.element(a,'Mean',1,TRUE) > a<-table.element(a,'Median',1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Lower Bound',1,TRUE) > a<-table.element(a,b$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/374yx1289838652.tab") > > try(system("convert tmp/1pckj1289838652.ps tmp/1pckj1289838652.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.805 0.175 1.225