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Data:
-4483.592838 -4642.372689 -4838.847424 -5040.46077 -4850.598143 -4806.134656 -5388.033015 -4987.408778 -5596.09098 -6513.501801 -7026.35819 -6932.059651 -8710.984942 -10286.65026 -10536.06841 -13401.59691 -12720.01639 -14758.70399 -19759.33364 -17082.38369 -25204.40303 -53473.56064 -533854.518 79964.4174 42900.581 67740.0525 46891.87093 82834.98699 1002202.245 369405.6774 -1405538.181 522230.6674 89126.53922 34483.04518 21948.21747 23397.25327 18443.57832 18722.3487 17617.49116 16549.70171 13952.43997 13540.98762 14506.52086 13245.89019 12092.74561 9120.933435 8315.807923 8210.018329 7453.921303 7464.41041 7534.226917 7844.435244 8341.584581 9025.764722 8684.589831 8843.29442 7605.314397 5977.279704 4023.149798 3838.307734
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R Code
par1 <- as(par1,'numeric') par2 <- as(par2,'numeric') par3 <- as(par3,'numeric') library(Hmisc) myseq <- seq(par1, par2, par3) hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE) bitmap(file='test1.png') plot(myseq,hd,col=2,main=main,xlab=xlab,ylab=ylab) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Harrell-Davis Quantiles',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'quantiles',header=TRUE) a<-table.element(a,'value',header=TRUE) a<-table.element(a,'standard error',header=TRUE) a<-table.row.end(a) length(hd) for (i in 1:length(hd)) { a<-table.row.start(a) a<-table.element(a,as(labels(hd)[i],'numeric'),header=TRUE) a<-table.element(a,as.matrix(hd[i])[1,1]) a<-table.element(a,as.matrix(attr(hd,'se')[i])[1,1]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')
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Big Analytics Cloud Computing Center
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