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Data:
0.9 0.92 0.92 0.95 1.06 1.17 1.23 1.26 1.37 1.37 1.31 1.21 1.2 1.11 1.11 1.11 1.17 1.08 1.05 1.03 1.04 1.02 1.01 1.01 0.98 0.96 0.94 0.99 0.99 0.98 1.02 1.06 1.06 1.06 1.06 1.06 1.04 1.02 1.01 1 1.04 1.09 1.08 1.06 1.06 1.03 0.97 0.98 0.93 0.88 0.86 0.9 0.91 0.93 0.89 0.88 0.83 0.81 0.83 0.8 0.76 0.73 0.74 0.74 0.75 0.74 0.74 0.73 0.71 0.71 0.7 0.75 0.81 0.78 0.75
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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
R Server
Big Analytics Cloud Computing Center
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