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Data:
-23.3833764438933 -8.55369733834187 -50.3530220901441 89.5334348554787 -68.566933218857 86.242991763873 91.1758987865468 -57.1463127299465 -104.147135994488 -61.3377568510805 93.9145973273952 -246.62370215812 -22.1898126799184 -35.0611543091103 -4.45883059064469 -177.531815680632 -70.5226787901682 30.5321994632175 -59.3912661927892 -131.127471928268 147.133618349113 45.6533837866806 -117.560608741138 117.383543115194 42.6617317274835 99.8038986352813 -7.78557246740002 -18.6816630538886 -116.476931578921 30.8852870895393 -33.7926636813331 215.707130826284 -6.57698871610461 -139.888187738920 25.1565120254716 12.3820264525211 178.787501612010 47.6458102812544 101.853055555168 88.3034658024652 116.005563628025 -75.7381551318659 16.1273126776685 93.9835410356264 -76.8562136700045 -48.1236206869778 11.2891165486600 124.570195756798
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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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