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Data:
547084.00 639842.00 770730.00 911599.00 971249.00 925102.00 906046.00 1006991.00 1013942.00 991188.00 819356.00 793778.00 601962.00 685640.00 785923.00 954888.00 1029140.00 972811.00 951330.00 1012865.00 1005502.00 987489.00 828421.00 817308.00 625827.00 683491.00 848657.00 978027.00 1019467.00 980306.00 992574.00 1080411.00 1047988.00 1023560.00 871245.00 824793.00 645999.00 736888.00 874488.00 992614.00 1107708.00 955938.00 1024122.00 1081598.00 1028158.00 1006457.00 826725.00 839116.00 591481.00 671244.00 788395.00 912291.00 987428.00 873452.00 952046.00 1037521.00 958597.00 965368.00 780741.00 814377.00 594739.00 668940.00 815882.00 928023.00 1025552.00 945840.00 1020639.00 1109899.00 1033403.00 1050530.00 840420.00 820378.00 609379.00 678402.00 889241.00 998445.00 1054502.00 1076699.00 1093802.00 1134793.00 1054084.00 1068675.00 857337.00 855380.00
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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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