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Data:
1772.2 1769.5 1768 1794.8 1823.4 1856.9 1866.9 1869.8 1843.8 1837.1 1857.7 1840.3 1914.6 1972.9 2050.1 2086.2 2112.5 2147.6 2190.4 2194.1 2216.2 2218.6 2233.5 2307.2 2350.4 2368.2 2353.8 2316.5 2305.5 2308.4 2334.4 2381.2 2449.7 2490.3 2523.5 2537.6 2526.1 2545.9 2542.7 2584.3 2600.2 2593.9 2618.9 2591.3 2521.2 2536.6 2596.1 2656.6 2710.3 2778.8 2775.5 2785.2 2847.7 2834.4 2839 2802.6 2819.3 2872 2918.4 2977.8 3031.2 3064.7 3093 3100.6 3141.1 3180.4 3240.3 3265 3338.2 3376.6 3422.5 3432 3516.3 3564 3636.3 3724 3815.4 3828.1 3853.3 3884.5 3918.7 3919.6 3950.8 3981 4063 4132 4160.3 4178.3 4244.1 4256.5 4283.4 4263.3 4256.6 4264.3 4302.3 4256.6 4374 4398.8 4433.9 4446.3 4525.8 4633.1 4677.5 4754.5 4876.2 4932.6 4906.3 4953.1 4909.6 4922.2 4873.5 4854.3 4795.3 4831.9 4913.3 4977.5 5090.7 5128.9 5154.1 5191.5 5251.8 5356.1 5451.9 5450.8 5469.4 5684.6 5740.3 5816.2 5825.9 5831.4 5873.3 5889.5 5908.5 5787.4 5776.6 5883.5 6005.7 5957.8 6030.2 5955.1 5857.3 5889.1 5866.4 5871 5944 6077.6 6197.5 6325.6 6448.3 6559.6 6623.3 6677.3 6740.3 6797.3 6903.5 6955.9 7022.8 7051 7119 7153.4 7193 7269.5 7332.6 7458 7496.6 7592.9 7632.1 7734 7806.6 7865 7927.4 7944.7 8027.7 8059.6 8059.5 7988.9 7950.2 8003.8 8037.5 8069 8157.6 8244.3 8329.4 8417 8432.5 8486.4 8531.1 8643.8 8727.9 8847.3 8904.3 9003.2 9025.3 9044.7 9120.7 9184.3 9247.2 9407.1 9488.9 9592.5 9666.2 9809.6 9932.7 10008.9 10103.4 10194.3 10328.8 10507.6 10601.2 10684 10819.9 11014.3 11043 11258.5 11267.9 11334.5 11297.2 11371.3 11340.1 11380.1 11477.9 11538.8 11596.4 11598.8 11645.8 11738.7 11935.5 12042.8 12127.6 12213.8 12303.5 12410.3 12534.1 12587.5 12683.2 12748.7 12915.9 12962.5 12965.9 13060.7 13099.9 13204 13321.1 13391.2 13366.9 13415.3 13324.6 13141.9 12925.4 12901.5 12973 13155
# 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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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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