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Data:
-0.00213797156751883 5.64632078561098e-05 0.000425419016811437 0.000897466029154824 -0.000382045448186076 0.000534880261745128 -0.000847667215332511 -0.000914841232112041 -6.08564196974725e-06 0.00131277756462814 0.000590448388309298 0.000349044409742462 0.00214807641135322 0.000878445427659102 0.00129082511551092 -0.00324794594081596 0.00193683772590134 0.000451555473426014 -2.27464893504349e-06 0.00230530591472807 0.00168793473865499 -0.00196783110490191 -0.000258346500677246 0.00229101492681159 -0.00112923585618114 0.000154270564877017 -0.00238808197915909 -0.000190353243549546 -0.000331524911271102 0.00079860605135158 -0.00086213794482144 0.00239651541010905 -0.00300964430430922 -0.000203228840023079 0.00099079544533456 -0.000374663342121463 0.000341268405796853 -0.00234910279440510 -0.00209148629793021 -0.00279978047993124 -0.00164203145816499 -0.00299653857733739 -0.000818279104627617 0.000325444946747244 -0.000476929259776715 0.00197871074205203 -0.000590864851984563 7.752264780303e-05
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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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