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Data:
0.91 0.9 0.89 0.89 0.89 0.89 0.89 0.89 0.88 0.88 0.88 0.86 0.85 0.85 0.86 0.9 0.92 0.91 0.93 0.96 0.96 0.97 0.98 1.01 0.99 1.03 1.08 1.06 1.1 1.17 1.16 1.12 1.17 1.13 1.12 1.07 1.04 1.08 1.06 1.12 1.18 1.13 1.08 1.06 1.09 1.02 1.01 1.01 1 1.01 1.03 1.09 1.07 1.05 1.06 1.06 1.08 1.07 1.04 1.04 1.06 1.09 1.09 1.05 1.01 1.02 1.03 1.06 1.08 1.05 1.05 1.05 1.04 1.05 1.07 1.1 1.16 1.16 1.17 1.17 1.18 1.21 1.18 1.13 1.12 1.17 1.19 1.26 1.25 1.28 1.35 1.39 1.45 1.41 1.32 1.31
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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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