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Data:
0.930232 -3.40521 2.02182 1.36969 -3.79215 -3.37923 -1.23382 3.31456 3.26075 -0.165989 -4.14243 -0.0335755 -5.40131 1.74607 -0.986595 -0.309542 1.91394 -0.327325 -0.89044 -2.14762 0.791583 -3.57304 2.88251 -2.73464 1.69646 0.902231 -3.62451 2.53148 3.31196 -0.604015 0.720093 -0.824376 0.429387 -4.31361 -0.823784 -2.52619 1.55265 0.929294 -0.0289107 1.74827 -2.28123 -0.525751 -3.45105 -0.167651 1.71842 -0.437273 3.83774 -1.61331 2.23669 -2.01368 4.19201 2.83074 0.877681 -1.05345 0.0338844 0.299579 2.82962 0.134707 -5.45701 4.75094 0.386812 2.65834 -2.6914 1.48738 -0.597236 2.58097 -2.44384 0.583801 -1.73785 -0.934774 2.46862 1.39291 -0.717696 1.43155 -0.856457 3.77396 -4.06016 1.74878 0.903159 1.95283 0.784645 0.322499 -1.6619 0.118537 3.16621 0.390905 -4.71432 -0.766198 1.02652 1.98851 2.11668 -1.09769 2.04049 3.91253 -4.32922 -1.18636 -1.20051 -2.32142 -1.32521 -3.74392 2.09449 3.67999 -2.24686 1.8847 -0.00138148 -0.561207 -1.10791 4.06735 -1.52051 3.86172 -4.82336 -1.81619 -0.673258 0.986615 1.79907 -6.14221 0.571834 3.01493 2.35191 -1.29061 1.30383 -3.13186 1.86218 -2.27961 2.06061 1.25248 4.74694 -3.25767 -0.605609 1.25981 -2.05434 1.74765 1.25994 1.73564 -1.85395 1.10537 0.938882 0.27089 -0.636737 3.25287 -1.69574 1.49124 0.0988109 -0.207916 3.28949 0.804418 2.87297 0.859365 0.272281 1.31216 -0.22338 -2.44715 0.153112 -1.1713 1.80552 -5.87528 1.33443 2.2369 -0.781063 1.36043 -0.629536 1.79828 1.09999 -2.85353 -2.49528 2.25146 0.520604 0.298607 6.90909 1.28231 -0.262004 1.46464 1.88438 -1.00143 -3.14066 0.777597 2.59824 -1.46655 -0.635298 -0.585772 2.72724 -0.934081 2.22985 -0.851462 -3.65571 -2.27573 -2.09533 2.38629 -0.0258131 -1.94653 0.438568 2.79009 -1.83582 -1.66756 -0.150236 -2.58702 1.49501 -2.89766 3.28964 -0.539803 0.420198 -2.1092 -0.188277 1.23821 0.941709 0.680047 0.382231 -1.0876 -0.493543 -0.135096 1.36667 -1.43758 0.420898 -0.779616 2.42003 1.67243 -0.386505 0.797683 -2.59059 -1.38176 -0.683298 -0.61428 1.34484 -1.2397 2.23363 -1.38525 -1.19997 1.99217 -4.27211 -0.765358 3.03439 2.60945 2.85029 2.76506 1.67524 3.62737 3.33055 3.50751 2.3026 -0.102461 -2.16051 -2.02834 -6.2928 0.131149 -1.42492 -1.0441 -0.61441 -1.15373 -2.18959 0.749191 1.95535 4.11493 -2.56849 -1.11805 0.561115 0.950764 0.930866 -0.344856 -1.97857 -1.62219 -0.138047 1.19406 -1.63891 0.204536 -4.23402 -5.46786 -1.83774 -6.51794 -0.928453 -1.83875 -3.75041 1.18437 1.22329 -0.0406617 -0.662308 1.62326 2.03548 -1.03108 0.847509 -0.66061 0.603647 0.92984 0.508684 0.00407915 0.725297 -2.63265
# 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')
Compute
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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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