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940 1070 1060 1070 1070 1040 950 1120 1150 1040 1040 1120 1000 960 1060 1060 1110 1030 960 1130 1150 1030 1040 1030 1070 1000 1020 1100 1080 990 1000 1110 1170 1030 1100 1020 1090 990 1060 1120 1030 1050 1030 1130 1140 980 1150 990 1020 1060 1080 1180 980 960 1020 1170 1150 950 1160 1120 1010 1010 1060 1130 1000 1000 1070 1150 1080 980 1210 1020 980 1030 1050 1190 970 950 1070 1170 1050 960 1300 1080 1030 1030 1070 1260 990 950 1080 1190 1050 950 1250 1140 1080 1020 1140 1320 1100 1040 1090 1280 1030 930 1280 1020
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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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