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Data:
1.84 1.89 1.71 1.43 1.28 1.29 1.76 2.78 2.75 3.11 3.03 2.8 2.78 2.04 2.03 1.32 0.93 1.09 1.47 1.99 2.77 2.42 2.05 2.24 2.18 2.11 2.9 2.71 1.45 1.47 1.9 1.87 2.98 2.51 2.41 2.24 2.36 2.18 2.6 1.57 1.38 1.33 1.47 2.41 3.81 3.86 2.58 2.61 2.18 2.03 2.17 1.26 1.3 1.17 1.49 2.09 2.76 2.16 1.95 2.36 2.53 2.23 1.95 1.6 1.33 1.36 1.39 2.25 3.13 2.54 2.17 2.11 2.11 1.88 2.39 1.38 0.97 1.11 1.39 1.94 2.47 1.82 1.99 2.38 2.21 2.13 1.8 1.22 1.02 1.17 1.6 2.12 3 2.23 1.87 2.13
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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
2 seconds
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Big Analytics Cloud Computing Center
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