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Data:
-8.562588494131 221.642856091557 -152.48274526826 295.631250866022 317.118100889547 -272.065153300428 -14.8911319732101 134.225573619448 131.486177290809 -107.822113400649 104.741638059487 279.215487949002 496.186928352294 -324.111248904754 -298.562955901744 -641.712675847783 -24.8910851554117 -531.786980093806 152.134386114004 -121.429262659234 -20.5827941224789 -129.708384681747 -153.062792958801 -127.954891211699 -272.138798428518 -57.2895952084763 -124.205153974969 21.2083131083458 -284.818339608561 146.246868934219 280.030736090634 -57.3677724459189 -275.906476161225 190.158355560676 51.4573378554693 -175.800101466085 86.0424180765638 147.446641495974 -425.922352836852 535.10665827592 -398.986716135688 8.57742619624186 118.765828913917 6.89595219366377 291.377902834559 -324.472992242067 -153.663488486180 -49.5166719532124 -531.768563328771
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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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