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Data:
-0.488399 0.255808 -0.186125 0.320883 0.393149 -0.123977 -0.454936 -0.163254 -0.234585 0.315784 0.0130534 -0.223887 0.370063 -0.360923 -0.15303 -0.175245 0.0398728 -0.164754 0.144993 -0.149785 0.124197 -0.32803 0.348919 -0.0989053 -0.147267 -0.440958 -0.408703 -0.251195 0.319684 -0.400873 0.288353 0.307179 0.60582 -0.219987 0.103435 -0.13759 0.315228 0.543727 0.0632975 0.058023 -0.203453 0.330273 -0.151718 0.0121755 -0.43381 0.105633 -0.149379 0.0681825 -0.235978 -0.710379 0.0986947 0.0883681 0.370829 -0.44999 0.488395 -0.484624 0.128524 0.0846028 0.350228 -0.386669 -0.411451 0.14764 -0.418541 0.300747 0.101746 0.147228 -0.180858 0.267838 0.308677 0.474163 0.313293 0.0464136 -0.469437 -0.188928 -0.216832 0.310743 -0.200895 -0.438967 0.0557948 0.213303 -0.435254 0.0533301 0.228512 -0.197451 0.207736 -0.482107 -0.419238 -0.488864 -0.194186 0.0629988 -0.434371 -0.454393 0.285177 0.272406 0.0710038 -0.177558 0.238798 0.0237009 -0.420761 -0.401727 0.32632 -0.158753 0.596711 -0.359842 0.345666 0.598968 -0.462647 -0.173287 0.0655658 0.255855 0.342298 0.0306006 0.0527948 0.311461 -0.205951 0.0340914 -0.223996 0.0638229 0.25075 0.222702 0.536084 -0.210141 0.332732 -0.39267 -0.18314 0.542756 0.499128 -0.210386 0.352234 -0.119761 0.0985749 0.0390797 -0.190961 -0.19665 0.538648 0.548975 0.573405 0.273745 -0.179567 0.241569 0.0683372 -0.463387 0.515036 0.302734 0.29515 0.308334 0.0599758 -0.435403 -0.234618 0.248282 -0.212131 -0.533668 -0.2594 -0.312867 -0.0949919 -0.0401132 -0.0288831 -0.0202405
# simulations
blockwidth of bootstrap
Significant digits
Quantiles
Unknown
P1 P5 Q1 Q3 P95 P99
P0.5 P2.5 Q1 Q3 P97.5 P99.5
P10 P20 Q1 Q3 P80 P90
bandwidth
Chart options
R Code
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) boot.stat <- function(s) { s.mean <- mean(s) s.median <- median(s) s.midrange <- (max(s) + min(s)) / 2 c(s.mean, s.median, s.midrange) } (r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed')) bitmap(file='plot1.png') plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean') grid() dev.off() bitmap(file='plot2.png') plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median') grid() dev.off() bitmap(file='plot3.png') plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange') grid() dev.off() bitmap(file='plot4.png') densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean') dev.off() bitmap(file='plot5.png') densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median') dev.off() bitmap(file='plot6.png') densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange') dev.off() z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3])) colnames(z) <- list('mean','median','midrange') bitmap(file='plot7.png') boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency') grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Estimation Results of Blocked Bootstrap',6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'statistic',header=TRUE) a<-table.element(a,'Q1',header=TRUE) a<-table.element(a,'Estimate',header=TRUE) a<-table.element(a,'Q3',header=TRUE) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,'IQR',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) q1 <- quantile(r$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$t[,2]))) a<-table.element(a,q3-q1) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'midrange',header=TRUE) q1 <- quantile(r$t[,3],0.25)[[1]] q3 <- quantile(r$t[,3],0.75)[[1]] a<-table.element(a,q1) a<-table.element(a,r$t0[3]) a<-table.element(a,q3) a<-table.element(a,sqrt(var(r$t[,3]))) a<-table.element(a,q3-q1) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Raw Input
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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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