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Data:
203.7 173.8 167.1 151.8 144.5 128.4 121.6 124.9 122.7 148.1 176.9 234.6 254.6 279.7 275.8 283 295.4 297.6 276.8 250.1 239.1 258.9 276.1 264.1 265.5 287.7 285.1 304.5 301.5 274.2 258.6 253.9 269.6 266.9 269.6 257.9 258.2 254.7 237.2 267.2 228.8 196.3 194.8 186.6 176.7 162.1 154.9 150.1 150.5 143.6 143.8 141.5 147.9 151.4 144.6 140.4 139.5 138.1 136.7 130 128.5 130.4 125.7 121.7 129.9 129.6 128.2 119.7 112.2 105.6 101.2 94.9 95.1 93.1 91.4 89.8 85.9 89.7 91.6 88.6 86.9 86.4 82.2 81.5 81.2
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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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Raw Output
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Computing time
2 seconds
R Server
Big Analytics Cloud Computing Center
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