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Data:
10.47 10.44 10.41 10.37 10.38 10.38 10.37 10.41 10.44 10.43 10.47 10.49 10.53 10.63 10.66 10.66 10.64 10.65 10.61 10.6 10.61 10.63 10.63 10.61 10.7 10.69 10.62 10.62 10.63 10.62 10.53 10.51 10.5 10.52 10.47 10.43 10.35 10.31 10.25 10.26 10.2 10.13 10.06 10.01 9.95 9.92 9.87 9.83 9.7 9.63 9.56 9.53 9.47 9.4 9.32 9.26 9.19 9.1 9.03 8.95 8.85 8.78 8.71 8.61 8.54 8.49 8.42 8.36 8.3 8.19 8.15 8.1 8.04 8.05 8.04 8 8.02 8 8 8.01 8.04 8.1 8.14 8.17 8.17 8.22 8.21 8.29 8.37 8.43 8.47 8.51 8.55 8.59 8.66 8.71 8.78 8.81 8.84 8.81 8.82 8.84 8.83 8.83 8.88 8.88 8.89 8.93 8.95 8.92 8.97 8.99 9.01 8.99 9.03 9.04 9.07 9.04 9.07 9.09 9.04 9.08 9.13 9.09 9.05 9.06 8.99 8.98 8.99 8.94 8.87 8.83 8.8 8.79 8.71 8.6 8.5 8.38 8.26 8.23 8.17 8.1 8.02 7.9 7.82 7.72 7.63 7.53 7.56 7.49 7.53 7.47 7.39 7.37 7.34 7.39 7.32 7.24 7.18 7.31 7.39 7.48 7.51 7.61 7.69 7.86 8.05 8.24 8.55 8.81 9.13 9.24 9.36 9.48 9.61 9.7 9.82 9.86 9.87 9.87
# simulations
blockwidth of bootstrap
Significant digits
Quantiles
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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R Server
Big Analytics Cloud Computing Center
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