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30 28 38 30 22 26 25 18 11 26 25 38 44 30 40 34 47 30 31 23 36 36 30 25 39 34 31 31 33 25 33 35 42 43 30 33 13 32 36 0 28 14 17 32 30 35 20 28 28 39 34 26 39 39 33 28 4 39 18 14 29 44 21 16 28 35 28 38 23 36 32 29 25 27 36 28 23 40 23 40 28 34 33 28 34 30 33 22 38 26 35 8 24 29 20 29 45 37 33 33 25 32 29 28 28 31 52 21 24 41 33 32 19 20 31 31 32 18 23 17 20 12 17 30 31 10 13 22 42 1 9 32 11 25 36 31 0 24 13 8 13 19 18 33 40 22 38 24 8 35 43 43 14 41 38 45 31 13 28 31 40 30 16 37 30 35 32 27 20 18 31 31 21 39 41 13 32 18 39 14 7 17 0 30 37 0 5 1 16 32 24 17 11 24 22 12 19 13 17 15 16 24 15 17 18 20 16 16 18 22 8 17 18 16 23 22 13 13 16 16 20 22 17 18 17 12 7 17 14 23 17 14 15 17 21 18 18 17 17 16 15 21 16 14 15 17 15 15 10 6 22 21 1 18 17 4 10 16 16 9 16 17 7 15 14 14 18 12 16 21 19 16 1 16 10 19 12 2 14 17 19 14 11 4 16 20 12 15 16
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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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2 seconds
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Big Analytics Cloud Computing Center
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