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Data:
0.000122731418385286 0.00241176062065143 0.00454140599615316 -0.00402583570154451 -0.00193967048183182 0.00320768442262351 0.00240051297617237 0.00248102399927561 0.00522120378512577 0.00323471226552284 -0.000422193121621420 0.000205816117153402 -0.000288091582987664 -0.00637508628400539 -0.00105104102454469 0.00743350631311348 -0.00767101170632287 0.00116401249609047 0.00117753419933191 0.000733275098580065 0.00384574338623112 -0.00307081652847713 -0.00264416152092356 -0.00279656278570905 -0.000702103656141851 -0.00745537201791366 -0.000425836473132485 -0.00293281614619538 -0.00125023796047494 -0.00092945793891733 0.000206465079581329 0.00164184814032768 0.00195746753848796 0.000127640171670621 -0.000542978626811696 4.06913608270088e-05 -0.00145098459719878 0.00219667743149766 0.000878446301642876 0.00143759416018860 8.37756048070314e-05 0.00595976943689932 -0.00163768348958786 0.00246577263478245 -0.000540183243434383 -0.000830262865008054 0.00211426862775146 0.00164418409853329 -0.00229453957395615
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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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