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Data:
-0.628162412817692 -2.46301447929447 -3.75038661297768 0.801641810798906 1.31725030274473 6.07651176840064 6.94589828224875 -0.198358189201074 -2.73650956748366 -0.152997113685818 -3.20400612400917 -1.34586197071795 -1.33516693443564 -1.74900223484405 -0.302676976651547 1.86822531243473 5.14212695982147 -0.11134249999139 -0.851495053263853 -3.32267426707525
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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,signif(as.matrix(hd[i])[1,1],6)) a<-table.element(a,signif(as.matrix(attr(hd,'se')[i])[1,1],6)) 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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