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Data:
-0.000170474174683904 0.00300105105514765 -0.00258118056597717 -0.00100474530085886 -0.00188317259190206 0.00226741260984998 -0.000378236771890163 0.00534467868598725 -0.00454122647204378 -0.000243030964403188 -0.00178877611418487 0.00196315202134216 0.00198733873263326 -0.00252514472141311 0.00111821256310272 0.00387688819377798 -0.00188036114794339 -0.00192385337153380 0.000588655014479161 -0.000374525152491403 0.000869024529743859 -0.000669663589467674 -0.00177170780798301 -0.00183025621937770 0.00365996468188564 -0.000200519045054502 0.000198305771384854 -0.000492380458504018 -0.00197714776666268 -0.00267978689994471 0.00474728909441552 -0.00309143062740757 0.000469148868372284 -0.00164114198064576 0.00129373584013251 0.00226179950814353 -0.00070068049122048 0.00262387467614701 0.008073000601554 0.0036133062200368 0.00426263030262271 -0.000185564534509172 -0.00263152838693195 0.00116617910298652 0.00161552901276068 -0.00137625725324675 -0.00407050694199777 -0.000573356069464514
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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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