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Data:
14.15 13.95 13.96 13.99 14.08 14.03 13.93 13.95 13.94 14.01 13.98 13.84 14.16 13.92 13.97 14 14 13.87 13.94 13.98 13.95 14.01 13.96 13.88 13.76 13.79 13.97 13.84 13.94 13.97 13.92 13.87 13.9 13.85 13.7 13.87 13.74 13.64 13.83 13.88 14.01 13.98 14.02 14.1 14.11 14.14 14.04 14.19 14.17 14.14 13.94 14.09 14.06 14.07 14.07 14.07 14.05 13.99 13.85 13.95 14.13 14.2 14.2 14.18 14.13 14.07 14.06 14.07 14.1 14.1 14 14.16 13.85 13.97 13.91 13.9 13.83 13.9 13.79 13.88 13.94 13.95 14.08 13.87 14.16 13.9 13.74 13.82 13.82 13.88 13.9 14.04 13.92 13.96 13.8 13.74 13.84 13.71 13.78 13.78 13.76 13.81 13.87 13.76 13.82 13.82 13.83 13.91 13.92 14 13.99 14.01 14.09 14.13 14.03 14.1 14.05 14.02 14.11 14.21 14.38 14.23 14.1 14.04 14.12 14 14.11 14.03 14.03 14.04 14.06 14.1 14.11 14.12 14.24 14.17 14.08 14.07 14.09 14.02 14.01 13.98 13.92 14.03 14.01 14.19 13.73 13.92 13.94 14.03 14.04 14.03 14.07 14.04 13.93 14.17 14.06 14.2 14.16 14.11 14.16 14.13 14.01 14.05 14.04 14.1 14.05 14.02 14.11 14.21 14.38 14.23 14.1 14.04 14.12 14 14.11 14.03 14.03 14.04 14.06 14.1 14.11 14.12 14.24 14.17 14.08 14.07 14.09 14.02 14.01 13.98 13.92 14.03 14.01 14.19 13.73 13.92 13.94 14.03 14.04 14.03 14.07 14.04 13.93 14.17 14.06 14.2 14.16 14.11 14.16 14.13 14.01 14.05 14.04 14.03 14.04 13.9 14.09 14.16 14.09 14.08 13.95 14.01 14 13.99 14 14.02 14.06 14.02 13.97 14.19 13.97 13.98 14.03 14.04 14.13 14.22 14.21 14.15 14.17 14.03 14.02 13.91 13.81 13.78 13.83 13.96 13.9 14.1 13.99 13.9 13.88 13.89 14.03 14.19 14.16 14.1 14.03 14.06 14.07 14.11 14.17 14.23 14.11 14.25 14.03 14.07 13.99 14.01 13.98 13.93 14.06 13.98 14 13.86 13.98 13.8 13.8 13.89 13.88 13.78 13.89 13.93 13.95 13.92 13.96 13.91 13.76 13.79 13.99 13.99 13.99 14.04 14.01 14.13 14.01 14.07 14.04 14.18 14.26 14.31 14.26 14.2 14.18 14.14 14.08 14 14.04 14.08 14 13.94 13.83 13.75 13.92 13.91 13.91 13.9 13.95 14.02 13.89 13.89 13.89 13.87 14.03 13.96 14.06 13.98 14.08 13.95 13.95 13.84 13.94 13.88 13.83 13.8 13.92 13.9 13.73 13.87 13.76 13.86 13.9 13.85 13.9 13.75 13.87 13.97 13.97 14.14 14.18 14.17 14.2 14.17 14.15 14.1 14.04 14.01 14.15 14.03 14.04 14.05 14.12 14.09 13.98 13.94 14.04 13.86 14.03 13.99 14.08 14.01 14.04 13.9 14.09 14.04 13.97 14.08 13.99 14.11 14.16 14.18 14.18 14.38 14.18 14.22 14.13 14.2 14.25 14.14 14.15 14.13 14.1 14.09 14.23 14.11 14.4 14.3 14.37 14.24 14.14 14.17 14.19 14.24 14.11 14.07 14.15 14.28 14.03 14.06 13.94 14.05 14.12 14 14.12 13.99 14.04 14.05 14.06 14.33 14.45 14.39 14.39 14.23 14.25 14.15 14.12 14.26 14.28 14.12 14.29 14.12 14.22 14.09 14.17 14.01 14.22 13.98 14.12 14.09 14.11 14.05 13.96 13.81 14.09 13.87 14.1 14.08 14.09 14.08 13.95 14.08 14 14.05 13.98 14.04 14.24 14.28 14.23 14.16 14.11 14.07 14.07 14.08 14.02 14.08 14.01 14.08 14.23 14.39 14.13 14.21 14.21 14.26 14.36 14.18 14.34 14.26 14.22 14.46 14.51 14.32 14.44 14.35 14.3 14.32 14.24 14.27 14.26 14.26 14.05 14.22 14.11 14.25 14.26 14.16 14.07 14.06 14.22 14.24 14.25 14.23 14.14 14.29 14.33 14.34 14.65 14.43 14.32 14.31 14.34 14.28 14.23 14.4 14.45 14.39 14.35 14.43 14.29 14.41 14.31 14.42 14.43 14.3 14.36 14.22 14.16 14.2 14.38 14.37 14.34 14.19 14.22 14.15 14 14.01 13.94 14 13.93 14.13 14.28 14.26 14.3 14.18 14.18 14.1 14.09 14.03 14.02 14.16 14 14.14 14.28 13.94 14.25 14.26 14.22 14.29 14.2 14.19 14.25 14.38 14.37 14.29 14.44 14.7 14.44 14.34 14.11 14.33 14.46 14.37 14.24 14.42 14.37 14.26 14.23 14.43 14.25 14.2 14.21 14.18 14.3 14.32 14.16 14.15 14.28 14.31 14.27 14.31 14.46 14.33 14.31 14.43 14.28 14.36 14.45 14.5 14.55 14.53 14.55 14.83 14.56 14.58 14.59 14.59 14.67 14.6 14.43 14.42 14.4 14.51 14.45 14.64 14.27 14.28 14.23 14.28 14.26 14.27 14.25 14.3 14.32 14.37 14.21 14.49 14.46 14.5 14.3 14.31 14.28 14.37 14.29 14.21 14.21 14.19 14.38 14.4 14.56 14.42 14.47 14.45 14.46 14.45 14.45 14.43 14.68 14.47 14.74 14.75 14.81 14.54 14.51 14.43 14.53 14.43 14.46 14.48 14.51 14.33
# simulations
Significant digits
Bandwidth
(?)
Quantiles
two.sided
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) } x<-na.omit(x) (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
Summary of computational transaction
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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