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Data:
-197.501 328.234 -0.85699 -0.209592 -163.587 -190.418 -0.534087 -240.851 -318.999 -832.044 -321.012 -233.688 -651.662 -378.328 -455.629 -425.768 -663.345 -258.025 115.501 -163.971 344.805 0.477897 149.641 -171.834 0.310933 -139.735 444.804 226.219 393.165 -112.638 552.174 0.636516 0.0374935 -115.944 111.035 370.351 0.8673 487.645 250.049 -108.665 -0.232926 25.642 0.150539 243.128 366.325 -0.559198 -15.286 -15.055 -201.284 212.894 -396.535 464.984 0.00492432 124.106 0.432189 15.778 146.032 -169.742 253.523 228.736 -180.463 602.771 313.887 -268.558 -138.867 427.311 -118.692 126.397 -449.502 121.558 179.721 -126.571 -298.754 -0.782106 -129.653 154.323 528.524 -429.999 157.818 211.868 567.838 315.768 -446.022 -17.432 -549.295 -273.099 -0.892859 -248.069 124.577 324.644 -152.078 0.81486 244.111 25.891 -262.064 259.135 -201.432 177.106 316.565 150.541 30.818 -403.543
# 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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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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