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Data:
19.31 19.47 19.7 19.76 19.9 19.97 20.1 20.26 20.44 20.43 20.57 20.6 20.69 20.93 20.98 21.11 21.14 21.16 21.32 21.32 21.48 21.58 21.74 21.75 21.81 21.89 22.21 22.37 22.47 22.51 22.55 22.61 22.58 22.85 22.93 22.98 23.01 23.11 23.18 23.18 23.21 23.22 23.12 23.15 23.16 23.21 23.21 23.22 23.25 23.39 23.41 23.45 23.46 23.44 23.54 23.62 23.86 24.07 24.13 24.12 24.17 24.23 24.28 24.12 24.14 24.17 24.2 24.36 24.34 24.38 24.46 24.6 24.63 24.75 24.64 24.69 24.7 24.74 24.87 24.92 24.94 24.98 25.13 25.15
# 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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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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