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Data:
145 621 262 208 362 424 339 736 291 58 498 643 390 332 750 368 659 234 396 300 343 536 543 217 298 1103 406 254 862 204 206 250 21 298 350 800 726 370 536 291 808 543 149 350 242 198 213 296 317 482 155 802 200 282 573 388 250 396 572
# 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) c(s.mean, s.median) } (r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed')) z <- data.frame(cbind(r$t[,1],r$t[,2])) colnames(z) <- list('mean','median') bitmap(file='plot7.png') b <- boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency') grid() dev.off() b 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.end(a) table.save(a,file='mytable.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='mytable1.tab')
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Big Analytics Cloud Computing Center
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