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Data:
2.7 3 -0.3 1.1 1.7 1.6 3 3.3 6.7 5.6 6 4.8 5.9 4.3 3.7 5.6 1.7 3.2 3.6 1.7 0.5 2.1 1.5 2.7 1.4 1.2 2.3 1.6 4.7 3.5 4.4 3.9 3.5 3 1.6 2.2 4.1 4.3 3.5 1.8 0.6 -0.4 -2.5 -1.6 -1.9 -1.6 -0.7 -1.1 0.3 1.3 3.3 2.4 2 3.9 4.2 4.9 5.8 4.8 4.4 5.3 2.1 2 -0.9 0.1 -0.5 -0.1 0.7 -0.4 -1.5 -0.3 1 0.4 0.3 1.8 3 2.2 3.4 3.4 3.1 4.5 4.6 5.7 4.3 4.5
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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
3 seconds
R Server
Big Analytics Cloud Computing Center
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