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Type 'q()' to quit R. > x <- c(0.96,0.95,0.95,0.96,0.96,0.96,0.95,0.96,0.96,0.96,0.95,0.95,0.96,0.96,0.96,0.96,0.96,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.96,0.96,0.96,0.97,0.97,0.97,0.96,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.94,0.94,0.94,0.93,0.93,0.93,0.93,0.92,0.93) > 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* 0.951091 -2.290909e-05 0.003231221 t2* 0.950000 8.600000e-04 0.003078857 > 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/10qvo1289852193.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,] 0.9427273 0.95 [2,] 0.9490909 0.95 [3,] 0.9514545 0.95 [4,] 0.9534545 0.95 [5,] 0.9576364 0.95 $n [1] 500 500 $conf [,1] [,2] [1,] 0.9511462 0.95 [2,] 0.9517629 0.95 $out [1] 0.9405455 0.9414545 0.9421818 0.9600000 0.9600000 0.9600000 0.9600000 [8] 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 [15] 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 [22] 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 [29] 0.9600000 0.9600000 0.9600000 0.9400000 0.9600000 0.9600000 0.9400000 [36] 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 0.9400000 [43] 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 0.9600000 [50] 0.9600000 0.9400000 0.9600000 0.9600000 0.9600000 $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 $names [1] "mean" "median" > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Estimation Results of Blocked Bootstrap',6,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'statistic',header=TRUE) > a<-table.element(a,'Q1',header=TRUE) > a<-table.element(a,'Estimate',header=TRUE) > a<-table.element(a,'Q3',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'IQR',header=TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'mean',header=TRUE) > q1 <- quantile(r$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$t[,2]))) > a<-table.element(a,q3-q1) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/2x0be1289852193.tab") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'95% Confidence Intervals',3,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'',1,TRUE) > a<-table.element(a,'Mean',1,TRUE) > a<-table.element(a,'Median',1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Lower Bound',1,TRUE) > a<-table.element(a,b$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/3i0rl1289852193.tab") > > try(system("convert tmp/10qvo1289852193.ps tmp/10qvo1289852193.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.665 0.195 0.854