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Data:
-0.203371 1.83954 -3.99842 -3.54979 1.99535 2.47494 0.491011 -1.06717 -2.40548 0.497605 -4.96832 -1.19681 -3.32339 1.45495 0.0324611 -1.52205 -0.895006 4.27043 -0.532763 0.344667 -0.766884 3.30913 -1.76993 0.667426 -2.96608 0.611989 -1.13864 0.268181 -0.0694413 4.24212 -0.2916 1.66636 -0.169951 2.75267 -0.286787 1.80494 1.12226 2.94223 2.78156 -0.234387 4.30637 -3.39222 2.62824 -3.48627 -1.77293 5.03519 -0.131355 1.33328 0.961863 3.08047 0.87483 -3.40977 -0.0697041 -0.353665 -4.67409 -0.267995 1.90704 -3.57494 -1.11979 -0.527631 -0.134618 -3.1628 1.73693 -8.62592 -2.1841 3.96131 3.54727 -2.74729 0.516192 0.665353 1.96648 -4.34254 0.198455 2.28418 1.80142 -3.45617 -0.59196 2.05281 -1.51061 3.38987 0.645193 1.11523 -1.05139 0.913353 0.3663 -1.1055 -1.76182 3.44819 -4.76006 1.60361 -0.164952 -1.46406 5.11849 0.807546 3.18599 0.507788 0.726992 -0.290257 -0.817927 -0.0100989 4.00474 -4.57783 -0.426452 3.76331 1.50891 1.31086 -1.03203 1.89323 0.444468 -2.24862 -2.51039 1.39191 1.90086 0.722152 2.60669 2.59014 -1.63463 1.89309 2.78846 0.164052 -4.39915 1.35566 2.70636 -0.481726 1.4205 1.44723 2.94503 -1.89198 3.95074 0.768292 -6.26729 -3.85708 -0.76368 3.36079 -0.120031 -0.436506 0.219161 3.45397 -1.56933 -0.495751 -1.02855 -3.1601 1.27308 -3.32889 3.97453 -0.699685 -0.00667291 -1.51653 0.0312629 1.38456 1.2778 3.36525 0.128356 -1.02979 1.05131 0.0723306 0.818199 -4.1199 -0.729021 3.42905 1.92781 -2.77076 1.67204 -3.84477 -0.451414 -0.508117 -1.20322 1.72267 4.15216 -2.86415 -0.188474 3.31753 -6.05261 -0.898591 3.272 3.69014 1.28913 3.45901 2.23509 1.70036 3.92907 5.43171 1.33328 -0.0097872 -0.439357 -2.82121 -8.79276 -1.31713 -0.6039 -2.44398 -0.435604 -2.49312 -2.95265 1.53202 2.71388 -1.87747 0.0818738 0.611181 0.623405 -0.256333 0.197445 -0.993439 -3.84957 0.0675354 -0.719349 -1.2423 0.736092 -5.0831 -6.41785 -2.72363 -5.87623 -1.85687 -2.3713 -3.05836 1.5444 1.99207 -0.710742 -0.0456103 2.16158 2.75577 -2.48705 2.3506 -0.786099 0.557902 1.49737 0.677204 -0.208789 1.40129
# simulations
Significant digits
Bandwidth
(?)
Quantiles
P1 P5 Q1 Q3 P95 P99
P1 P5 Q1 Q3 P95 P99
P0.5 P2.5 Q1 Q3 P97.5 P99.5
P10 P20 Q1 Q3 P80 P90
Chart options
R Code
par1 <- as.numeric(par1) par2 <- as.numeric(par2) if (par3 == '0') bw <- NULL if (par3 != '0') bw <- as.numeric(par3) if (par1 < 10) par1 = 10 if (par1 > 5000) par1 = 5000 library(modeest) library(lattice) library(boot) boot.stat <- function(s,i) { s.mean <- mean(s[i]) s.median <- median(s[i]) s.midrange <- (max(s[i]) + min(s[i])) / 2 s.mode <- mlv(s[i], method='mfv')$M s.kernelmode <- mlv(s[i], method='kernel', bw=bw)$M c(s.mean, s.median, s.midrange, s.mode, s.kernelmode) } (r <- boot(x,boot.stat, R=par1, stype='i')) 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$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange') grid() dev.off() bitmap(file='plot7.png') plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode') grid() dev.off() bitmap(file='plot8.png') plot(r$t[,5],type='p',ylab='simulated values',main='Simulation of Mode of Kernel Density') grid() dev.off() bitmap(file='plot4.png') densityplot(~r$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() bitmap(file='plot9.png') densityplot(~r$t[,4],col='black',main='Density Plot',xlab='mode') dev.off() bitmap(file='plot10.png') densityplot(~r$t[,5],col='black',main='Density Plot',xlab='mode of kernel dens.') dev.off() z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3],r$t[,4],r$t[,5])) colnames(z) <- list('mean','median','midrange','mode','mode k.dens') bitmap(file='plot11.png') boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency') grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Estimation Results of Bootstrap',10,TRUE) a<-table.row.end(a) if (par4 == 'P1 P5 Q1 Q3 P95 P99') { myq.1 <- 0.01 myq.2 <- 0.05 myq.3 <- 0.95 myq.4 <- 0.99 myl.1 <- 'P1' myl.2 <- 'P5' myl.3 <- 'P95' myl.4 <- 'P99' } if (par4 == 'P0.5 P2.5 Q1 Q3 P97.5 P99.5') { myq.1 <- 0.005 myq.2 <- 0.025 myq.3 <- 0.975 myq.4 <- 0.995 myl.1 <- 'P0.5' myl.2 <- 'P2.5' myl.3 <- 'P97.5' myl.4 <- 'P99.5' } if (par4 == 'P10 P20 Q1 Q3 P80 P90') { myq.1 <- 0.10 myq.2 <- 0.20 myq.3 <- 0.80 myq.4 <- 0.90 myl.1 <- 'P10' myl.2 <- 'P20' myl.3 <- 'P80' myl.4 <- 'P90' } a<-table.row.start(a) a<-table.element(a,'statistic',header=TRUE) a<-table.element(a,myl.1,header=TRUE) a<-table.element(a,myl.2,header=TRUE) a<-table.element(a,'Q1',header=TRUE) a<-table.element(a,'Estimate',header=TRUE) a<-table.element(a,'Q3',header=TRUE) a<-table.element(a,myl.3,header=TRUE) a<-table.element(a,myl.4,header=TRUE) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,'IQR',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) q1 <- quantile(r$t[,1],0.25)[[1]] q3 <- quantile(r$t[,1],0.75)[[1]] p01 <- quantile(r$t[,1],myq.1)[[1]] p05 <- quantile(r$t[,1],myq.2)[[1]] p95 <- quantile(r$t[,1],myq.3)[[1]] p99 <- quantile(r$t[,1],myq.4)[[1]] a<-table.element(a,signif(p01,par2)) a<-table.element(a,signif(p05,par2)) a<-table.element(a,signif(q1,par2)) a<-table.element(a,signif(r$t0[1],par2)) a<-table.element(a,signif(q3,par2)) a<-table.element(a,signif(p95,par2)) a<-table.element(a,signif(p99,par2)) a<-table.element( a,signif( sqrt(var(r$t[,1])),par2 ) ) a<-table.element(a,signif(q3-q1,par2)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'median',header=TRUE) q1 <- quantile(r$t[,2],0.25)[[1]] q3 <- quantile(r$t[,2],0.75)[[1]] p01 <- quantile(r$t[,2],myq.1)[[1]] p05 <- quantile(r$t[,2],myq.2)[[1]] p95 <- quantile(r$t[,2],myq.3)[[1]] p99 <- quantile(r$t[,2],myq.4)[[1]] a<-table.element(a,signif(p01,par2)) a<-table.element(a,signif(p05,par2)) a<-table.element(a,signif(q1,par2)) a<-table.element(a,signif(r$t0[2],par2)) a<-table.element(a,signif(q3,par2)) a<-table.element(a,signif(p95,par2)) a<-table.element(a,signif(p99,par2)) a<-table.element(a,signif(sqrt(var(r$t[,2])),par2)) a<-table.element(a,signif(q3-q1,par2)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'midrange',header=TRUE) q1 <- quantile(r$t[,3],0.25)[[1]] q3 <- quantile(r$t[,3],0.75)[[1]] p01 <- quantile(r$t[,3],myq.1)[[1]] p05 <- quantile(r$t[,3],myq.2)[[1]] p95 <- quantile(r$t[,3],myq.3)[[1]] p99 <- quantile(r$t[,3],myq.4)[[1]] a<-table.element(a,signif(p01,par2)) a<-table.element(a,signif(p05,par2)) a<-table.element(a,signif(q1,par2)) a<-table.element(a,signif(r$t0[3],par2)) a<-table.element(a,signif(q3,par2)) a<-table.element(a,signif(p95,par2)) a<-table.element(a,signif(p99,par2)) a<-table.element(a,signif(sqrt(var(r$t[,3])),par2)) a<-table.element(a,signif(q3-q1,par2)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mode',header=TRUE) q1 <- quantile(r$t[,4],0.25)[[1]] q3 <- quantile(r$t[,4],0.75)[[1]] p01 <- quantile(r$t[,4],myq.1)[[1]] p05 <- quantile(r$t[,4],myq.2)[[1]] p95 <- quantile(r$t[,4],myq.3)[[1]] p99 <- quantile(r$t[,4],myq.4)[[1]] a<-table.element(a,signif(p01,par2)) a<-table.element(a,signif(p05,par2)) a<-table.element(a,signif(q1,par2)) a<-table.element(a,signif(r$t0[4],par2)) a<-table.element(a,signif(q3,par2)) a<-table.element(a,signif(p95,par2)) a<-table.element(a,signif(p99,par2)) a<-table.element(a,signif(sqrt(var(r$t[,4])),par2)) a<-table.element(a,signif(q3-q1,par2)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mode k.dens',header=TRUE) q1 <- quantile(r$t[,5],0.25)[[1]] q3 <- quantile(r$t[,5],0.75)[[1]] p01 <- quantile(r$t[,5],myq.1)[[1]] p05 <- quantile(r$t[,5],myq.2)[[1]] p95 <- quantile(r$t[,5],myq.3)[[1]] p99 <- quantile(r$t[,5],myq.4)[[1]] a<-table.element(a,signif(p01,par2)) a<-table.element(a,signif(p05,par2)) a<-table.element(a,signif(q1,par2)) a<-table.element(a,signif(r$t0[5],par2)) a<-table.element(a,signif(q3,par2)) a<-table.element(a,signif(p95,par2)) a<-table.element(a,signif(p99,par2)) a<-table.element(a,signif(sqrt(var(r$t[,5])),par2)) a<-table.element(a,signif(q3-q1,par2)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Big Analytics Cloud Computing Center
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