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Data:
0.11 0.28 0.30 0.20 0.34 0.50 0.10 0.51 0.36 0.16 0.39 0.21 0.27 0.11 0.15 0.15 0.53 0.45 0.20 0.10 0.13 0.19 0.31 0.26 0.47 0.19 0.34 0.19 0.12 0.17 0.25 0.24 0.22 0.13 0.23 0.44 0.21 0.03 0.11 0.15 0.27 0.15 0.17 0.43 0.30 0.16 0.22 0.27 0.23 0.38 0.14 0.08 0.51 0.35 0.16 0.14 0.18 0.21 0.14 0.33 0.39 0.18 0.32 0.34 0.25 0.06
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highest quantile
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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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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