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Data:
25.94 28.66 33.95 31.01 21.00 26.19 25.41 30.47 12.88 9.78 8.25 7.44 10.81 9.12 11.03 12.74 9.98 11.62 9.40 9.27 7.76 8.78 10.65 10.95 12.36 10.85 11.84 12.14 11.65 8.86 7.63 7.38 7.25 8.03 7.75 7.16 7.18 7.51 7.07 7.11 8.98 9.53 10.54 11.31 10.36 11.44 10.45 10.69 11.28 11.96 13.52 12.89 14.03 16.27 16.17 17.25 19.38 26.20 33.53 32.20 38.45 44.86 41.67 36.06 39.76 36.81 42.65 46.89 53.61 57.59 67.82 71.89 75.51 68.49 62.72 70.39 59.77 57.27 67.96 67.85 76.98 81.08 91.66 84.84 85.73 84.61 92.91 99.80 121.19 122.04 131.76 138.48 153.47 189.95 182.22 198.08 135.36 125.02 143.50 173.95 188.75 167.44 158.95 169.53 113.66 107.59 92.67 85.35 90.13 89.31 105.12 125.83 135.81 142.43 163.39 168.21 185.35 188.50 199.91 210.73 192.06 204.62 235.00 261.09 256.88 251.53 257.25 243.10 283.75 300.98
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R Code
library(Hmisc) m <- mean(x) e <- median(x) bitmap(file='test1.png') op <- par(mfrow=c(2,1)) mydensity1 <- density(x,kernel='gaussian',na.rm=TRUE) plot(mydensity1,main='Density Plot - Gaussian Kernel',xlab='Median (0 -> full line) | Mean (0 -> dashed line)',ylab='density') abline(v=e,lty=1) abline(v=m,lty=5) grid() myseq <- seq(0.01, 0.99, 0.01) hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE) plot(myseq,hd,col=2,main='Harrell-Davis Quantiles',xlab='quantiles',ylab='Median (0 -> full) | Mean (0 -> dashed)') abline(h=m,lty=5) abline(h=e,lty=1) grid() par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Median versus Mean',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,mean(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'median',header=TRUE) a<-table.element(a,median(x)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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